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  • WPF WriteableBitmap

    - by Sam
    I'm using WriteableBitmap on an image of type Bgra32 to change the pixel value of certain pixels. I'm setting the value to 0x77CCCCCC. After calling WritePixels, the pixels I set to 0x77CCCCCC show up with a value of 0x77FFFFFF. Why does this happen? How do I make the pixels have the correct value?

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  • Basic image resizing in Ruby on Rails

    - by Koning Baard XIV
    I'm creating a little photo sharing site for our home's intranet, and I have an upload feature, which uploads the photo at original size into the database. However, I also want to save the photo in four other sizes: W=1024, W=512, W=256 and W=128, but only the sizes smaller than the original size (e.g. if the original width is 511, only generate 256 and 128). How can I implement this? I already have this code to upload the photo: pic.rb <-- model def image_file=(input_data) self.filename = input_data.original_filename self.content_type = input_data.content_type.chomp self.binary_data = input_data.read # here it should generate the smaller sizes #+and save them to self.binary_data_1024, etc... end new.rb <-- view <h1>New pic</h1> <% form_for(@pic, :html => {:multipart => true}) do |f| %> <%= f.error_messages %> <p> <%= f.label :title %><br /> <%= f.text_field :title %> </p> <p> <%= f.label :description %><br /> <%= f.text_field :description %> </p> <p> <%= f.label :image_file %><br /> <%= f.file_field :image_file %> </p> <p> <%= f.submit 'Create' %> </p> <% end %> <%= link_to 'Back', pics_path %> Thanks

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  • libpng cannot read an image properly

    - by jonathanasdf
    Here is my function... I don't know why it's not working. The resulting image looks nothing like what the .png looks like. But there's no errors either. bool Bullet::read_png(std::string file_name, int pos) { png_structp png_ptr; png_infop info_ptr; FILE *fp; if ((fp = fopen(file_name.c_str(), "rb")) == NULL) { return false; } png_ptr = png_create_read_struct(PNG_LIBPNG_VER_STRING, NULL, NULL, NULL); if (png_ptr == NULL) { fclose(fp); return false; } info_ptr = png_create_info_struct(png_ptr); if (info_ptr == NULL) { fclose(fp); png_destroy_read_struct(&png_ptr, NULL, NULL); return false; } if (setjmp(png_jmpbuf(png_ptr))) { png_destroy_read_struct(&png_ptr, &info_ptr, NULL); fclose(fp); return false; } png_init_io(png_ptr, fp); png_read_png(png_ptr, info_ptr, PNG_TRANSFORM_STRIP_16 | PNG_TRANSFORM_SWAP_ALPHA | PNG_TRANSFORM_EXPAND, NULL); png_uint_32 width = png_get_image_width(png_ptr, info_ptr); png_uint_32 height = png_get_image_height(png_ptr, info_ptr); imageData[pos].width = width; imageData[pos].height = height; png_bytepp row_pointers; row_pointers = png_get_rows(png_ptr, info_ptr); imageData[pos].data = new unsigned int[width*height]; for (unsigned int i=0; i < height; ++i) { memcpy(&imageData[pos].data[i*width], &row_pointers[i], width*sizeof(unsigned int)); } png_destroy_read_struct(&png_ptr, &info_ptr, NULL); fclose(fp); for (unsigned int i=0; i < height; ++i) { for (unsigned int j=0; j < width; ++j) { unsigned int val = imageData[pos].data[i*width+j]; if (val != 0) { unsigned int a = ((val >> 24)); unsigned int r = (((val - (a << 24)) >> 16)); unsigned int g = (((val - (a << 24) - (r << 16)) >> 8)); unsigned int b = (((val - (a << 24) - (r << 16) - (g << 8)))); // for debugging std::string s(AS3_StringValue(AS3_Int(i*width+j))); s += " "; s += AS3_StringValue(AS3_Int(val)); s += " "; s += AS3_StringValue(AS3_Int(a)); s += " "; s += AS3_StringValue(AS3_Int(r)); s += " "; s += AS3_StringValue(AS3_Int(g)); s += " "; s += AS3_StringValue(AS3_Int(b)); AS3_Trace(AS3_String(s.c_str())); } } } return true; } ImageData is just a simple struct to keep x, y, width, and height, and imageData is an array of that struct. struct ImageData { int x; int y; int width; int height; unsigned int* data; }; Here is a side by side screenshot of the input and output graphics (something I made in a minute for testing), and this was after setting alpha to 255 in order to make it show up (because the alpha I was getting back was 1). Left side is original, right side is what happened after reading it through this function. Scaled up 400% for visibility. Here is a log of the traces: 0 16855328 1 1 49 32 1 16855424 1 1 49 128 2 16855456 1 1 49 160 3 16855488 1 1 49 192 4 16855520 1 1 49 224 5 16855552 1 1 50 0 6 16855584 1 1 50 32 7 16855616 1 1 50 64 8 16855424 1 1 49 128 9 16855456 1 1 49 160 10 16855488 1 1 49 192 11 16855520 1 1 49 224 12 16855552 1 1 50 0 13 16855584 1 1 50 32 14 16855616 1 1 50 64 15 16855648 1 1 50 96 16 16855456 1 1 49 160 17 16855488 1 1 49 192 18 16855520 1 1 49 224 19 16855552 1 1 50 0 20 16855584 1 1 50 32 21 16855616 1 1 50 64 22 16855648 1 1 50 96 23 16855680 1 1 50 128 24 16855488 1 1 49 192 25 16855520 1 1 49 224 26 16855552 1 1 50 0 27 16855584 1 1 50 32 28 16855616 1 1 50 64 29 16855648 1 1 50 96 30 16855680 1 1 50 128 31 16855712 1 1 50 160 32 16855520 1 1 49 224 33 16855552 1 1 50 0 34 16855584 1 1 50 32 35 16855616 1 1 50 64 36 16855648 1 1 50 96 37 16855680 1 1 50 128 38 16855712 1 1 50 160 39 16855744 1 1 50 192 40 16855552 1 1 50 0 41 16855584 1 1 50 32 42 16855616 1 1 50 64 43 16855648 1 1 50 96 44 16855680 1 1 50 128 45 16855712 1 1 50 160 46 16855744 1 1 50 192 47 16855776 1 1 50 224 48 16855584 1 1 50 32 49 16855616 1 1 50 64 50 16855648 1 1 50 96 51 16855680 1 1 50 128 52 16855712 1 1 50 160 53 16855744 1 1 50 192 54 16855776 1 1 50 224 55 16855808 1 1 51 0 56 16855616 1 1 50 64 57 16855648 1 1 50 96 58 16855680 1 1 50 128 59 16855712 1 1 50 160 60 16855744 1 1 50 192 61 16855776 1 1 50 224 62 16855808 1 1 51 0 63 16855840 1 1 51 32 64 16855648 1 1 50 96 65 16855680 1 1 50 128 66 16855712 1 1 50 160 67 16855744 1 1 50 192 68 16855776 1 1 50 224 69 16855808 1 1 51 0 70 16855840 1 1 51 32 71 16855872 1 1 51 64 72 16855680 1 1 50 128 73 16855712 1 1 50 160 74 16855744 1 1 50 192 75 16855776 1 1 50 224 76 16855808 1 1 51 0 77 16855840 1 1 51 32 78 16855872 1 1 51 64 79 16855904 1 1 51 96 80 16855712 1 1 50 160 81 16855744 1 1 50 192 82 16855776 1 1 50 224 83 16855808 1 1 51 0 84 16855840 1 1 51 32 85 16855872 1 1 51 64 86 16855904 1 1 51 96 87 16855936 1 1 51 128 88 16855744 1 1 50 192 89 16855776 1 1 50 224 90 16855808 1 1 51 0 91 16855840 1 1 51 32 92 16855872 1 1 51 64 93 16855904 1 1 51 96 94 16855936 1 1 51 128 95 16855968 1 1 51 160 96 16855776 1 1 50 224 97 16855808 1 1 51 0 98 16855840 1 1 51 32 99 16855872 1 1 51 64 100 16855904 1 1 51 96 101 16855936 1 1 51 128 102 16855968 1 1 51 160 103 16856000 1 1 51 192 104 16855808 1 1 51 0 105 16855840 1 1 51 32 106 16855872 1 1 51 64 107 16855904 1 1 51 96 108 16855936 1 1 51 128 109 16855968 1 1 51 160 110 16856000 1 1 51 192 111 16856032 1 1 51 224 112 16855840 1 1 51 32 113 16855872 1 1 51 64 114 16855904 1 1 51 96 115 16855936 1 1 51 128 116 16855968 1 1 51 160 117 16856000 1 1 51 192 118 16856032 1 1 51 224 119 16856064 1 1 52 0 120 16855872 1 1 51 64 121 16855904 1 1 51 96 122 16855936 1 1 51 128 123 16855968 1 1 51 160 124 16856000 1 1 51 192 125 16856032 1 1 51 224 126 16856064 1 1 52 0 127 16856096 1 1 52 32 128 16855904 1 1 51 96 129 16855936 1 1 51 128 130 16855968 1 1 51 160 131 16856000 1 1 51 192 132 16856032 1 1 51 224 133 16856064 1 1 52 0 134 16856096 1 1 52 32 135 16856128 1 1 52 64 136 16855936 1 1 51 128 137 16855968 1 1 51 160 138 16856000 1 1 51 192 139 16856032 1 1 51 224 140 16856064 1 1 52 0 141 16856096 1 1 52 32 142 16856128 1 1 52 64 143 16856160 1 1 52 96 144 16855968 1 1 51 160 145 16856000 1 1 51 192 146 16856032 1 1 51 224 147 16856064 1 1 52 0 148 16856096 1 1 52 32 149 16856128 1 1 52 64 150 16856160 1 1 52 96 151 16856192 1 1 52 128 152 16856000 1 1 51 192 153 16856032 1 1 51 224 154 16856064 1 1 52 0 155 16856096 1 1 52 32 156 16856128 1 1 52 64 157 16856160 1 1 52 96 158 16856192 1 1 52 128 159 16856224 1 1 52 160 160 16856032 1 1 51 224 161 16856064 1 1 52 0 162 16856096 1 1 52 32 163 16856128 1 1 52 64 164 16856160 1 1 52 96 165 16856192 1 1 52 128 166 16856224 1 1 52 160 167 16856256 1 1 52 192 168 16856064 1 1 52 0 169 16856096 1 1 52 32 170 16856128 1 1 52 64 171 16856160 1 1 52 96 172 16856192 1 1 52 128 173 16856224 1 1 52 160 174 16856256 1 1 52 192 175 16856288 1 1 52 224 176 16856096 1 1 52 32 177 16856128 1 1 52 64 178 16856160 1 1 52 96 179 16856192 1 1 52 128 180 16856224 1 1 52 160 181 16856256 1 1 52 192 182 16856288 1 1 52 224 183 16856320 1 1 53 0 184 16856128 1 1 52 64 185 16856160 1 1 52 96 186 16856192 1 1 52 128 187 16856224 1 1 52 160 188 16856256 1 1 52 192 189 16856288 1 1 52 224 190 16856320 1 1 53 0 192 16856160 1 1 52 96 193 16856192 1 1 52 128 194 16856224 1 1 52 160 195 16856256 1 1 52 192 196 16856288 1 1 52 224 197 16856320 1 1 53 0 200 16856192 1 1 52 128 201 16856224 1 1 52 160 202 16856256 1 1 52 192 203 16856288 1 1 52 224 204 16856320 1 1 53 0 208 16856224 1 1 52 160 209 16856256 1 1 52 192 210 16856288 1 1 52 224 211 16856320 1 1 53 0 216 16856256 1 1 52 192 217 16856288 1 1 52 224 218 16856320 1 1 53 0 224 16856288 1 1 52 224 225 16856320 1 1 53 0 232 16856320 1 1 53 0 Was stuck on this for a couple of days.

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  • MPIexec.exe Access denide

    - by shake
    I have installed microsoft compute cluster and MPI.net, now i have trouble to run program using mpiexec.exe on cluster. When i try to run it on console i get message: "Access Denied", and pop up: "mpiexec.exe is not valid win32 application". I tried google it, but found nothing. Pls help. :)

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  • Java Imaging Framework

    - by Prabhakar
    Is there any Open source or Commercial Java frameworks for doing image operations such as converting the images from one format to other and scaling the images etc. There should be no installation.Set of jars that are in classpath that will do the job. I have looked into the java-image-scaling library but it is having issues. Thanks in advance.

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  • Number of threads and thread numbers in Grand Central Dispatch

    - by raphgott
    I am using C and Grand Central Dispatch to parallelize some heavy computations. How can I get the number of threads used by GCD? Also is it possible to know on which thread a piece of code is currently running on? Basically I'd like to use sprng (parallel random numbers) with multiple streams and for that I need to know what stream id to use (and therefore what thread is being used).

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  • Django-imagekit: how to reduce image quality with a preprocessor_spec ?

    - by pierre-guillaume-degans
    Hi, please excuse me for my ugly english :p I've created this simple model class, with a Preprocessor to reduce my photos'quality (the photos'extension is .JPG): from django.db import models from imagekit.models import ImageModel from imagekit.specs import ImageSpec from imagekit import processors class Preprocessor(ImageSpec): quality = 50 processors = [processors.Format] class Picture(ImageModel): image = models.ImageField(upload_to='pictures') class IKOptions: preprocessor_spec = Preprocessor The problem : pictures'quality are not reduced. :( Any idea to fix it ? Thank you very much ;)

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  • Run all SQL files in a directory

    - by Khalil Dahab
    I have a number of .sql files which I have to run in order to apply changes made by other developers on an SQL Server 2005 database. The files are named according to the following pattern: 0001 - abc.sql 0002 - abcef.sql 0003 - abc.sql ... Is there a way to run all of them in one go?

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  • How to use Haar wavelet to detect LINES on an image?

    - by Ole Jak
    So I have Image like this I want to get something like this (I hevent drawn all lines I want but I hope you can get my idea) I want to use SURF ( (Speeded Up Robust Features) is a robust image descriptor, first presented by Herbert Bay et al. in 2006 ) or something that is based on sums of 2D Haar wavelet responses and makes an efficient use of integral images for finding all straight lines on image. I want to get relative to picture pixel coords start and end points of lines. So on this picture to find all lines between tiles and thouse 2 black lines on top. Is there any such Code Example (with lines search capability) to start from? I love C and C++ but any other readable code will probably work for me=)

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  • Training sets for AdaBoost algorithm

    - by palau1
    How do you find the negative and positive training data sets of Haar features for the AdaBoost algorithm? So say you have a certain type of blob that you want to locate in an image and there are several of them in your entire array - how do you go about training it? I'd appreciate a nontechnical explanation as much as possible. I'm new to this. Thanks.

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  • Steganography Experiment - Trouble hiding message bits in DCT coefficients

    - by JohnHankinson
    I have an application requiring me to be able to embed loss-less data into an image. As such I've been experimenting with steganography, specifically via modification of DCT coefficients as the method I select, apart from being loss-less must also be relatively resilient against format conversion, scaling/DSP etc. From the research I've done thus far this method seems to be the best candidate. I've seen a number of papers on the subject which all seem to neglect specific details (some neglect to mention modification of 0 coefficients, or modification of AC coefficient etc). After combining the findings and making a few modifications of my own which include: 1) Using a more quantized version of the DCT matrix to ensure we only modify coefficients that would still be present should the image be JPEG'ed further or processed (I'm using this in place of simply following a zig-zag pattern). 2) I'm modifying bit 4 instead of the LSB and then based on what the original bit value was adjusting the lower bits to minimize the difference. 3) I'm only modifying the blue channel as it should be the least visible. This process must modify the actual image and not the DCT values stored in file (like jsteg) as there is no guarantee the file will be a JPEG, it may also be opened and re-saved at a later stage in a different format. For added robustness I've included the message multiple times and use the bits that occur most often, I had considered using a QR code as the message data or simply applying the reed-solomon error correction, but for this simple application and given that the "message" in question is usually going to be between 10-32 bytes I have plenty of room to repeat it which should provide sufficient redundancy to recover the true bits. No matter what I do I don't seem to be able to recover the bits at the decode stage. I've tried including / excluding various checks (even if it degrades image quality for the time being). I've tried using fixed point vs. double arithmetic, moving the bit to encode, I suspect that the message bits are being lost during the IDCT back to image. Any thoughts or suggestions on how to get this working would be hugely appreciated. (PS I am aware that the actual DCT/IDCT could be optimized from it's naive On4 operation using row column algorithm, or an FDCT like AAN, but for now it just needs to work :) ) Reference Papers: http://www.lokminglui.com/dct.pdf http://arxiv.org/ftp/arxiv/papers/1006/1006.1186.pdf Code for the Encode/Decode process in C# below: using System; using System.Collections.Generic; using System.Linq; using System.Text; using System.Drawing.Imaging; using System.Drawing; namespace ImageKey { public class Encoder { public const int HIDE_BIT_POS = 3; // use bit position 4 (1 << 3). public const int HIDE_COUNT = 16; // Number of times to repeat the message to avoid error. // JPEG Standard Quantization Matrix. // (to get higher quality multiply by (100-quality)/50 .. // for lower than 50 multiply by 50/quality. Then round to integers and clip to ensure only positive integers. public static double[] Q = {16,11,10,16,24,40,51,61, 12,12,14,19,26,58,60,55, 14,13,16,24,40,57,69,56, 14,17,22,29,51,87,80,62, 18,22,37,56,68,109,103,77, 24,35,55,64,81,104,113,92, 49,64,78,87,103,121,120,101, 72,92,95,98,112,100,103,99}; // Maximum qauality quantization matrix (if all 1's doesn't modify coefficients at all). public static double[] Q2 = {1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1}; public static Bitmap Encode(Bitmap b, string key) { Bitmap response = new Bitmap(b.Width, b.Height, PixelFormat.Format32bppArgb); uint imgWidth = ((uint)b.Width) & ~((uint)7); // Maximum usable X resolution (divisible by 8). uint imgHeight = ((uint)b.Height) & ~((uint)7); // Maximum usable Y resolution (divisible by 8). // Start be transferring the unmodified image portions. // As we'll be using slightly less width/height for the encoding process we'll need the edges to be populated. for (int y = 0; y < b.Height; y++) for (int x = 0; x < b.Width; x++) { if( (x >= imgWidth && x < b.Width) || (y>=imgHeight && y < b.Height)) response.SetPixel(x, y, b.GetPixel(x, y)); } // Setup the counters and byte data for the message to encode. StringBuilder sb = new StringBuilder(); for(int i=0;i<HIDE_COUNT;i++) sb.Append(key); byte[] codeBytes = System.Text.Encoding.ASCII.GetBytes(sb.ToString()); int bitofs = 0; // Current bit position we've encoded too. int totalBits = (codeBytes.Length * 8); // Total number of bits to encode. for (int y = 0; y < imgHeight; y += 8) { for (int x = 0; x < imgWidth; x += 8) { int[] redData = GetRedChannelData(b, x, y); int[] greenData = GetGreenChannelData(b, x, y); int[] blueData = GetBlueChannelData(b, x, y); int[] newRedData; int[] newGreenData; int[] newBlueData; if (bitofs < totalBits) { double[] redDCT = DCT(ref redData); double[] greenDCT = DCT(ref greenData); double[] blueDCT = DCT(ref blueData); int[] redDCTI = Quantize(ref redDCT, ref Q2); int[] greenDCTI = Quantize(ref greenDCT, ref Q2); int[] blueDCTI = Quantize(ref blueDCT, ref Q2); int[] blueDCTC = Quantize(ref blueDCT, ref Q); HideBits(ref blueDCTI, ref blueDCTC, ref bitofs, ref totalBits, ref codeBytes); double[] redDCT2 = DeQuantize(ref redDCTI, ref Q2); double[] greenDCT2 = DeQuantize(ref greenDCTI, ref Q2); double[] blueDCT2 = DeQuantize(ref blueDCTI, ref Q2); newRedData = IDCT(ref redDCT2); newGreenData = IDCT(ref greenDCT2); newBlueData = IDCT(ref blueDCT2); } else { newRedData = redData; newGreenData = greenData; newBlueData = blueData; } MapToRGBRange(ref newRedData); MapToRGBRange(ref newGreenData); MapToRGBRange(ref newBlueData); for(int dy=0;dy<8;dy++) { for(int dx=0;dx<8;dx++) { int col = (0xff<<24) + (newRedData[dx+(dy*8)]<<16) + (newGreenData[dx+(dy*8)]<<8) + (newBlueData[dx+(dy*8)]); response.SetPixel(x+dx,y+dy,Color.FromArgb(col)); } } } } if (bitofs < totalBits) throw new Exception("Failed to encode data - insufficient cover image coefficients"); return (response); } public static void HideBits(ref int[] DCTMatrix, ref int[] CMatrix, ref int bitofs, ref int totalBits, ref byte[] codeBytes) { int tempValue = 0; for (int u = 0; u < 8; u++) { for (int v = 0; v < 8; v++) { if ( (u != 0 || v != 0) && CMatrix[v+(u*8)] != 0 && DCTMatrix[v+(u*8)] != 0) { if (bitofs < totalBits) { tempValue = DCTMatrix[v + (u * 8)]; int bytePos = (bitofs) >> 3; int bitPos = (bitofs) % 8; byte mask = (byte)(1 << bitPos); byte value = (byte)((codeBytes[bytePos] & mask) >> bitPos); // 0 or 1. if (value == 0) { int a = DCTMatrix[v + (u * 8)] & (1 << HIDE_BIT_POS); if (a != 0) DCTMatrix[v + (u * 8)] |= (1 << HIDE_BIT_POS) - 1; DCTMatrix[v + (u * 8)] &= ~(1 << HIDE_BIT_POS); } else if (value == 1) { int a = DCTMatrix[v + (u * 8)] & (1 << HIDE_BIT_POS); if (a == 0) DCTMatrix[v + (u * 8)] &= ~((1 << HIDE_BIT_POS) - 1); DCTMatrix[v + (u * 8)] |= (1 << HIDE_BIT_POS); } if (DCTMatrix[v + (u * 8)] != 0) bitofs++; else DCTMatrix[v + (u * 8)] = tempValue; } } } } } public static void MapToRGBRange(ref int[] data) { for(int i=0;i<data.Length;i++) { data[i] += 128; if(data[i] < 0) data[i] = 0; else if(data[i] > 255) data[i] = 255; } } public static int[] GetRedChannelData(Bitmap b, int sx, int sy) { int[] data = new int[8 * 8]; for (int y = sy; y < (sy + 8); y++) { for (int x = sx; x < (sx + 8); x++) { uint col = (uint)b.GetPixel(x,y).ToArgb(); data[(x - sx) + ((y - sy) * 8)] = (int)((col >> 16) & 0xff) - 128; } } return (data); } public static int[] GetGreenChannelData(Bitmap b, int sx, int sy) { int[] data = new int[8 * 8]; for (int y = sy; y < (sy + 8); y++) { for (int x = sx; x < (sx + 8); x++) { uint col = (uint)b.GetPixel(x, y).ToArgb(); data[(x - sx) + ((y - sy) * 8)] = (int)((col >> 8) & 0xff) - 128; } } return (data); } public static int[] GetBlueChannelData(Bitmap b, int sx, int sy) { int[] data = new int[8 * 8]; for (int y = sy; y < (sy + 8); y++) { for (int x = sx; x < (sx + 8); x++) { uint col = (uint)b.GetPixel(x, y).ToArgb(); data[(x - sx) + ((y - sy) * 8)] = (int)((col >> 0) & 0xff) - 128; } } return (data); } public static int[] Quantize(ref double[] DCTMatrix, ref double[] Q) { int[] DCTMatrixOut = new int[8*8]; for (int u = 0; u < 8; u++) { for (int v = 0; v < 8; v++) { DCTMatrixOut[v + (u * 8)] = (int)Math.Round(DCTMatrix[v + (u * 8)] / Q[v + (u * 8)]); } } return(DCTMatrixOut); } public static double[] DeQuantize(ref int[] DCTMatrix, ref double[] Q) { double[] DCTMatrixOut = new double[8*8]; for (int u = 0; u < 8; u++) { for (int v = 0; v < 8; v++) { DCTMatrixOut[v + (u * 8)] = (double)DCTMatrix[v + (u * 8)] * Q[v + (u * 8)]; } } return(DCTMatrixOut); } public static double[] DCT(ref int[] data) { double[] DCTMatrix = new double[8 * 8]; for (int v = 0; v < 8; v++) { for (int u = 0; u < 8; u++) { double cu = 1; if (u == 0) cu = (1.0 / Math.Sqrt(2.0)); double cv = 1; if (v == 0) cv = (1.0 / Math.Sqrt(2.0)); double sum = 0.0; for (int y = 0; y < 8; y++) { for (int x = 0; x < 8; x++) { double s = data[x + (y * 8)]; double dctVal = Math.Cos((2 * y + 1) * v * Math.PI / 16) * Math.Cos((2 * x + 1) * u * Math.PI / 16); sum += s * dctVal; } } DCTMatrix[u + (v * 8)] = (0.25 * cu * cv * sum); } } return (DCTMatrix); } public static int[] IDCT(ref double[] DCTMatrix) { int[] Matrix = new int[8 * 8]; for (int y = 0; y < 8; y++) { for (int x = 0; x < 8; x++) { double sum = 0; for (int v = 0; v < 8; v++) { for (int u = 0; u < 8; u++) { double cu = 1; if (u == 0) cu = (1.0 / Math.Sqrt(2.0)); double cv = 1; if (v == 0) cv = (1.0 / Math.Sqrt(2.0)); double idctVal = (cu * cv) / 4.0 * Math.Cos((2 * y + 1) * v * Math.PI / 16) * Math.Cos((2 * x + 1) * u * Math.PI / 16); sum += (DCTMatrix[u + (v * 8)] * idctVal); } } Matrix[x + (y * 8)] = (int)Math.Round(sum); } } return (Matrix); } } public class Decoder { public static string Decode(Bitmap b, int expectedLength) { expectedLength *= Encoder.HIDE_COUNT; uint imgWidth = ((uint)b.Width) & ~((uint)7); // Maximum usable X resolution (divisible by 8). uint imgHeight = ((uint)b.Height) & ~((uint)7); // Maximum usable Y resolution (divisible by 8). // Setup the counters and byte data for the message to decode. byte[] codeBytes = new byte[expectedLength]; byte[] outBytes = new byte[expectedLength / Encoder.HIDE_COUNT]; int bitofs = 0; // Current bit position we've decoded too. int totalBits = (codeBytes.Length * 8); // Total number of bits to decode. for (int y = 0; y < imgHeight; y += 8) { for (int x = 0; x < imgWidth; x += 8) { int[] blueData = ImageKey.Encoder.GetBlueChannelData(b, x, y); double[] blueDCT = ImageKey.Encoder.DCT(ref blueData); int[] blueDCTI = ImageKey.Encoder.Quantize(ref blueDCT, ref Encoder.Q2); int[] blueDCTC = ImageKey.Encoder.Quantize(ref blueDCT, ref Encoder.Q); if (bitofs < totalBits) GetBits(ref blueDCTI, ref blueDCTC, ref bitofs, ref totalBits, ref codeBytes); } } bitofs = 0; for (int i = 0; i < (expectedLength / Encoder.HIDE_COUNT) * 8; i++) { int bytePos = (bitofs) >> 3; int bitPos = (bitofs) % 8; byte mask = (byte)(1 << bitPos); List<int> values = new List<int>(); int zeroCount = 0; int oneCount = 0; for (int j = 0; j < Encoder.HIDE_COUNT; j++) { int val = (codeBytes[bytePos + ((expectedLength / Encoder.HIDE_COUNT) * j)] & mask) >> bitPos; values.Add(val); if (val == 0) zeroCount++; else oneCount++; } if (oneCount >= zeroCount) outBytes[bytePos] |= mask; bitofs++; values.Clear(); } return (System.Text.Encoding.ASCII.GetString(outBytes)); } public static void GetBits(ref int[] DCTMatrix, ref int[] CMatrix, ref int bitofs, ref int totalBits, ref byte[] codeBytes) { for (int u = 0; u < 8; u++) { for (int v = 0; v < 8; v++) { if ((u != 0 || v != 0) && CMatrix[v + (u * 8)] != 0 && DCTMatrix[v + (u * 8)] != 0) { if (bitofs < totalBits) { int bytePos = (bitofs) >> 3; int bitPos = (bitofs) % 8; byte mask = (byte)(1 << bitPos); int value = DCTMatrix[v + (u * 8)] & (1 << Encoder.HIDE_BIT_POS); if (value != 0) codeBytes[bytePos] |= mask; bitofs++; } } } } } } } UPDATE: By switching to using a QR Code as the source message and swapping a pair of coefficients in each block instead of bit manipulation I've been able to get the message to survive the transform. However to get the message to come through without corruption I have to adjust both coefficients as well as swap them. For example swapping (3,4) and (4,3) in the DCT matrix and then respectively adding 8 and subtracting 8 as an arbitrary constant seems to work. This survives a re-JPEG'ing of 96 but any form of scaling/cropping destroys the message again. I was hoping that by operating on mid to low frequency values that the message would be preserved even under some light image manipulation.

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  • Finding what makes strings unique in a list, can you improve on brute force?

    - by Ed Guiness
    Suppose I have a list of strings where each string is exactly 4 characters long and unique within the list. For each of these strings I want to identify the position of the characters within the string that make the string unique. So for a list of three strings abcd abcc bbcb For the first string I want to identify the character in 4th position d since d does not appear in the 4th position in any other string. For the second string I want to identify the character in 4th position c. For the third string it I want to identify the character in 1st position b AND the character in 4th position, also b. This could be concisely represented as abcd -> ...d abcc -> ...c bbcb -> b..b If you consider the same problem but with a list of binary numbers 0101 0011 1111 Then the result I want would be 0101 -> ..0. 0011 -> .0.. 1111 -> 1... Staying with the binary theme I can use XOR to identify which bits are unique within two binary numbers since 0101 ^ 0011 = 0110 which I can interpret as meaning that in this case the 2nd and 3rd bits (reading left to right) are unique between these two binary numbers. This technique might be a red herring unless somehow it can be extended to the larger list. A brute-force approach would be to look at each string in turn, and for each string to iterate through vertical slices of the remainder of the strings in the list. So for the list abcd abcc bbcb I would start with abcd and iterate through vertical slices of abcc bbcb where these vertical slices would be a | b | c | c b | b | c | b or in list form, "ab", "bb", "cc", "cb". This would result in four comparisons a : ab -> . (a is not unique) b : bb -> . (b is not unique) c : cc -> . (c is not unique) d : cb -> d (d is unique) or concisely abcd -> ...d Maybe it's wishful thinking, but I have a feeling that there should be an elegant and general solution that would apply to an arbitrarily large list of strings (or binary numbers). But if there is I haven't yet been able to see it. I hope to use this algorithm to to derive minimal signatures from a collection of unique images (bitmaps) in order to efficiently identify those images at a future time. If future efficiency wasn't a concern I would use a simple hash of each image. Can you improve on brute force?

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  • Video match anlysis

    - by Mohammad
    Hi every body I am looking forward to find an algorithm to detect a pattern in a given video file. Actually I am going to index moments in a tennis match video at which service (first kick after a goal) is shot. PS1: sorry for broken English. PS2: I DO NOT know anything about tennis except that you need a ball to play!!

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  • Will the values of label and its correspondences change if Image is rotated?

    - by Vinayak Agarwal
    Hi all I have an image in which a text like "VINAYAK 123" is written. The text in the image is at a certain angle, say 30degrees. Now when I extract the labels of the connected components, I get V-1, I-2, N-3, A-4,Y-5,A-6,K-7, 1-8,2-9,3-10( Format: Character- Label No.). Now I rotate the image 30 degrees in the clockwise direction to make the text in the image horizontal. My question is that now if I extract the labels of the connected components, will the character and the label no. correspondence still remain the same? Thanks in advance!

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  • Coordinate geometry operations in images/discrete space

    - by avd
    I have images which have line segments, rays etc. I am representing these line segments using Bresenham algorithm (means whatever coordinates I get using this algorithm between two points). Now I want to do operations such as finding intersection point between two line segments, finding the projection of one vector onto other etc... The problem is I am not working in continuous space. The line segments are being approximated using Bresenham algorithm. So I want suggestions on what are the best and most efficient ways to do this? A link to C++ library or implementation would also be good enough. Please suggest some books which deal with such problems.

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  • Can anyone give me a sample DSP script in C/C++

    - by Andrew
    Im working on a (Audio) DSP project and just wondering if there are any sample (Open source) DSP example that are written in c or c++, for my MSP430 Chip. I just want something as a guideline so i can program my own script using the ACD and DCA on my board for sampling. http://focus.ti.com/docs/toolsw/folders/print/msp-exp430f5438.html Thats my board, MSP430F5438 Experimenter Board, from what i herd it can run dsp script via the USB connection with the computer. Im using CCS ( From TI, code composer studio) and Octave/Matlab. Just any DSP example scripts or sites that will help me create my own would be appreciated. What im tying to do, Partial audio (sampled) track -- Nyquist rate sampling -- over- and undersampling -- reconstruction of the audio track.

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  • How to generate a lower frequency version of a signal in Matlab?

    - by estourodepilha.com
    With a sine input, I tried to modify it's frequency cutting some lower frequencies in the spectrum, shifting the main frequency towards zero. As the signal is not fftshifted I tried to do that by eliminating some samples at the begin and at the end of the fft vector: interval = 1; samplingFrequency = 44100; signalFrequency = 440; sampleDuration = 1 / samplingFrequency; timespan = 1 : sampleDuration : (1 + interval); original = sin(2 * pi * signalFrequency * timespan); fourierTransform = fft(original); frequencyCut = 10; %% Hertz frequencyCut = floor(frequencyCut * (length(pattern) / samplingFrequency) / 4); %% Samples maxFrequency = length(fourierTransform) - (2 * frequencyCut); signal = ifft(fourierTransform(frequencyCut + 1:maxFrequency), 'symmetric'); But it didn't work as expected. I also tried to remove the center part of the spectrum, but it wielded a higher frequency sine wave too. How to make it right?

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  • Matlab: Analysis of signal

    - by Mateusz
    Hi, I have a problem with this task: For free route perform frequency analysis and give parametrs of each signal component: time of beginning and ending of each component beginning and ending frequency amplitude (in time domain) in the beginning and end of each signal's component level of noise in dB Assume, that, the parametrs of each component like amplitude, frequency is changing lineary in time. Frequency of sampling is 1000Hz For example I have signal like this: Nx=64; fs=1000; t=1/fs*(0:Nx-1); %========================== A1=1; A2=4; f1=500; f2=1000; x1=A1*cos(2*pi*f1*t); x2=A2*sin(2*pi*f2*t); %========================== x=x1+x2;

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  • php gdlib angle problem

    - by creativz
    I'm using php gd lib 5.2.13 and tried to make a picture with imagettftext ($image, $color and $font are defined of course). imagettftext($image, 12, 90, 10, 20, $black, $font, "This.is_a test 123"); //image, font size, angle, x value, y value, color, font, text As you can see I want the angle to be 90°. The problem is that the text is not beeing rotated properly, e.g. the dots are at the top (and not at the bottom) of the text. I read that this is a common issue and has been fixed in php gdlib 5.3, But since I have 5.2.13 running on a webhost (...) is there a solution to rotate it properly with using gdlib 5.2.13? Thanks!

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  • iPhone OS: Strategies for high density image work

    - by Jasconius
    I have a project that is coming around the bend this summer that is going to involve, potentially, an extremely high volume of image data for display. We are talking hundreds of 640x480-ish images in a given application session (scaled to a smaller resolution when displayed), and handfuls of very large (1280x1024 or higher) images at a time. I've already done some preliminary work and I've found that the typical 640x480ish image is just a shade under 1MB in memory when placed into a UIImageView and displayed... but the very large images can be a whopping 5+ MB's in some cases. This project is actually be targeted at the iPad, which, in my Instruments tests seems to cap out at about 80-100MB's of addressable physical memory. Details aside, I need to start thinking of how to move huge volumes of image data between virtual and physical memory while preserving the fluidity and responsiveness of the application, which will be high visibility. I'm probably on the higher ends of intermediate at Objective-C... so I am looking for some solid articles and advice on the following: 1) Responsible management of UIImage and UIImageView in the name of conserving physical RAM 2) Merits of using CGImage over UIImage, particularly for the huge images, and if there will be any performance gain 3) Anything dealing with memory paging particularly as it pertains to images I will epilogue by saying that the numbers I have above maybe off by about 10 or 15%. Images may or may not end up being bundled into the actual app itself as opposed to being loaded in from an external server.

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