SIFT.zip_SIFT 特征点_SIFT特征_feature extract_特征匹配_特征提取

/****************************************************** *欢迎到www.opencvchina.com下载源代码和资料 * Code by Utkarsh Sinha * Based on JIFT by Jun Liu * Visit http://aishack.in/ for more indepth articles and tutorials * on artificial intelligence * Use, reuse, modify, hack, kick. Do whatever you want with * this code :) ******************************************************/ #include "stdafx.h" #include <stdio.h> #include "SIFT.h" #define SIGMA_ANTIALIAS 0.5 #define SIGMA_PREBLUR 1.0 #define CURVATURE_THRESHOLD 5.0 #define CONTRAST_THRESHOLD 0.03 // in terms of 255 #define M_PI 3.1415926535897932384626433832795 #define NUM_BINS 36 #define MAX_KERNEL_SIZE 20 #define FEATURE_WINDOW_SIZE 16 #define DESC_NUM_BINS 8 #define FVSIZE 128 #define FV_THRESHOLD 0.2 // SaveFloatingPointImage() // The standard HighGUI functions can save only 8bit images. This // function converts a floating point image (with values 0..1) into // a normal 8bit image (with values 0..255), and then saves it. void SaveFloatingPointImage(const char *filename, IplImage* img) { IplImage* dup = cvCreateImage(cvGetSize(img), 8, 1); cvCvtScale(img, dup, 255.0); cvSaveImage(filename, dup); cvReleaseImage(&dup); } // Constructor: Give a preloaded image and provide the desired number // of octaves and intervals SIFT::SIFT(IplImage* img, int octaves, int intervals) { // Store the image internally m_srcImage = cvCloneImage(img); // Set the number of octaves and intervals m_numOctaves = octaves; m_numIntervals = intervals; // Proceed to initialize the algorithm GenerateLists(); } // Constructor: Give a filename and the desired number of octaves // and intervals SIFT::SIFT(const char* filename, int octaves, int intervals) { // Load the image m_srcImage = cvLoadImage(filename); // Set the number of octaves and intervals m_numOctaves = octaves; m_numIntervals = intervals; // Proceed to initialize the algorithm GenerateLists(); } // AllocateMemory() // This function allocates memory for the scale space (the multiple gaussian images, // the difference of guassian images) void SIFT::GenerateLists() { // A variable for the loops unsigned int i=0; // Create a 2D array of gaussian blurred images m_gList = new IplImage**[m_numOctaves]; for(i=0;i<m_numOctaves;i++) m_gList[i] = new IplImage*[m_numIntervals+3]; // Create a 2D array to store images generated after the // DoG operation m_dogList = new IplImage**[m_numOctaves]; for(i=0;i<m_numOctaves;i++) m_dogList[i] = new IplImage*[m_numIntervals+2]; // Create a 2D array that will hold if a particular point // is an extrema or not m_extrema = new IplImage**[m_numOctaves]; for(i=0;i<m_numOctaves;i++) m_extrema[i] = new IplImage*[m_numIntervals]; // Create a 2D array of decimal numbers. It holds the sigma // used to blur the gaussian images. m_absSigma = new double*[m_numOctaves]; for(i=0;i<m_numOctaves;i++) m_absSigma[i] = new double[m_numIntervals+3]; } // Destructor // Cleanup after you're done SIFT::~SIFT() { unsigned int i, j; for(i=0;i<m_numOctaves;i++) { // Release all images in that particular octave for(j=0;j<m_numIntervals+3;j++) cvReleaseImage(&m_gList[i][j]); for(j=0;j<m_numIntervals+2;j++) cvReleaseImage(&m_dogList[i][j]); for(j=0;j<m_numIntervals;j++) cvReleaseImage(&m_extrema[i][j]); // Delete memory for that array delete [] m_gList[i]; delete [] m_dogList[i]; delete [] m_extrema[i]; delete [] m_absSigma[i]; } // Delete the 2D arrays delete [] m_gList; delete [] m_dogList; delete [] m_extrema; delete [] m_absSigma; //printf("欢迎到www.opencvchina.com下载更多源代码和资料"); } // DoSift() // This function does everything in sequence. void SIFT::DoSift() { BuildScaleSpace(); DetectExtrema(); AssignOrientations(); ExtractKeypointDescriptors(); } // BuildScaleSpace() // This function generates all the blurred out images for each octave // and also the DoG images void SIFT::BuildScaleSpace() { printf("Generating scale space...\n"); // For loops unsigned int i,j; // floating point grayscale image IplImage* imgGray = cvCreateImage(cvGetSize(m_srcImage), IPL_DEPTH_32F , 1); IplImage* imgTemp = cvCreateImage(cvGetSize(m_srcImage), 8 , 1); // Create a duplicate. We don't want to mess the original // If the image is colour, it is converted to grayscale if(m_srcImage->nChannels==3) { cvCvtColor(m_srcImage, imgTemp, CV_BGR2GRAY); } else { cvCopy(m_srcImage, imgTemp); } // Finally, generate the floating point image... convert 0..255 range into 0..1 for(int x=0;x<imgTemp->width;x++) { for(int y=0;y<imgTemp->height;y++) { cvSetReal2D(imgGray, y, x, cvGetReal2D(imgTemp, y, x)/255.0); } } // Lowe claims blur the image with a sigma of 0.5 and double it's dimensions // to increase the number of stable keypoints cvSmooth(imgGray, imgGray, CV_GAUSSIAN, 0, 0, SIGMA_ANTIALIAS); // Create an image double the dimensions, resize imgGray and store it in m_gList[0][0] m_gList[0][0] = cvCreateImage(cvSize(imgGray->width*2, imgGray->height*2), IPL_DEPTH_32F , 1); cvPyrUp(imgGray, m_gList[0][0]); // Preblur this base image cvSmooth(m_gList[0][0], m_gList[0][0], CV_GAUSSIAN, 0, 0, SIGMA_PREBLUR); // SaveFloatingPointImage("C:\\SIFT Test\\Gaussian\\g_octave_0_scale_0.jpg", m_gList[0][0]); double initSigma = sqrt(2.0f); // Keep a track of the sigmas m_absSigma[0][0] = initSigma * 0.5; // Now for the actual image generation for(i=0;i<m_numOctaves;i++) { // Reset sigma for each octave double sigma = initSigma; CvSize currentSize = cvGetSize(m_gList[i][0]); for(j=1;j<m_numIntervals+3;j++) { // Allocate memory m_gList[i][j] = cvCreateImage(currentSize, 32, 1); // Calculate a sigma to blur the current image to get the next one double sigma_f = sqrt(pow(2.0,2.0/m_numIntervals)-1) * sigma; sigma = pow(2.0,1.0/m_numIntervals) * sigma; // Store sigma values (to be used later on) m_absSigma[i][j] = sigma * 0.5 * pow(2.0f, (float)i); // Apply gaussian smoothing) cvSmooth(m_gList[i][j-1], m_gList[i][j], CV_GAUSSIAN, 0, 0, sigma_f); // Calculate the DoG image m_dogList[i][j-1] = cvCreateImage(currentSize, 32, 1); cvSub(m_gList[i][j-1], m_gList[i][j], m_dogList[i][j-1]); // Save the images generated for fun :) /*char* filename = new char[200]; sprintf(filename, "C:\\SIFT Test\\Gaussian\\g_octave_%d_scale_%d.jpg", i, j); SaveFloatingPointImage(filename, m_gList[i][j]); sprintf(filename, "C:\\SIFT TEST\\DOG\\dog_octave_%d_scale_%d.jpg", i, j-1); SaveFloatingPointImage(filename, m_dogList[i][j-1]);*/ } // If we're not at the last octave if(i<m_numOctaves-1) { // Reduce size to half currentSize.width/=2; currentSize.height/=2; // Allocate memory and resample the image m_gList[i+1][0] = cvCreateImage(currentSize, 32, 1); cvPyrDown(m_gList[i][0], m_gList[i+1][0]); m_absSigma[i+1][0] = m_absSigma[i][m_numIntervals]; // Store the image /*char* filename = new char[200]; sprintf(filename, "C:\\SIFT Test\\Gaussian\\g_octave_%d_scale_0.jpg", i+1); SaveFloatingPointImage(filename, m_gList[i+1][0]);*/ } } } // DetectExtrema() // Locates extreme points (maxima and minima) // Relatively simple stuff void SIFT::DetectExtrema() { printf("Detecting extrema...\n"); // Looping variables unsigned int i, j, xi, yi; // Some variables we'll use later on double curvature_ratio, curvature_threshold; IplImage *middle, *up, *down; int scale; double dxx, dyy, dxy, trH, detH; unsigned int num=0; // Number of keypoins detected unsigned int numRemoved=0; // The number of key points rejected because they failed a test curvature_th