基于Java实现图片相似度对比的示例代码基于Java实现图片相似度对比的

前言
依赖
基本算法
相关代码

前言很多时候我们需要将两个图片进行对比，确定两个图片的相似度。一般常用的就是openCv库，这里就是使用openCv进行图片相似度对比。

依赖

org.bytedecojavacv1.3.3org.bytedecojavacv-platform1.3.3

基本算法基本算法
1、判断高度是否一致，如果不一致，需要截取到高度一致
2、截取算法
a、因为图片有通用的顶部bar和底部bar，需要先找到底部bar。
【基于Java实现图片相似度对比的示例代码】b、截取长图片的部分，然后和底部bar拼接，就完成了图片截取。
c、这里设置一个默认的宽度，然后对比，找到相同部分，就是底部bar。

相关代码

package com.test.image; import org.bytedeco.javacpp.BytePointer; import org.bytedeco.javacpp.opencv_core; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import static org.bytedeco.javacpp.opencv_core.*; import static org.bytedeco.javacpp.opencv_imgcodecs.imread; import static org.bytedeco.javacpp.opencv_imgcodecs.imwrite; import static org.bytedeco.javacpp.opencv_imgproc.*; import static org.bytedeco.javacpp.opencv_imgproc.THRESH_BINARY; public class ImageService {private static Logger Log = LoggerFactory.getLogger(ImageService.class); public static void compareImage( String targetImageUrl, String baseImageUrl ){ /*** 读取图片到数组*/opencv_core.Mat targetImage = imread(targetImageUrl); opencv_core.Mat baseImage = imread(baseImageUrl); Log.info("read image success"); /*** 首先对比的两个图片宽度要一致，否则不能对比*/if(targetImage.size().width()==baseImage.size().width()){ /*** 基本算法* 1、判断高度是否一致，如果不一致，需要截取到高度一致* 2、截取算法*a、因为图片有通用的顶部bar和底部bar，需要先找到底部bar。*b、截取长图片的部分，然后和底部bar拼接，就完成了图片截取。*c、这里设置一个默认的宽度，然后对比，找到相同部分，就是底部bar。*/ if(targetImage.size().height()!=baseImage.size().height()){ if(targetImage.size().height()>baseImage.size().height()){targetImage = dealLongImage(targetImage.clone(),baseImage.clone()); } else {baseImage = dealLongImage(baseImage.clone(),targetImage.clone()); }} /*** 进行图片差异对比*/Mat imageDiff = compareImage(targetImage,baseImage); double nonZeroPercent = 100 * (double) countNonZero(imageDiff) / (imageDiff.size().height() * imageDiff.size().width()); /*** 展示图片，将标准图，对比图，差异图，拼接成一张大图。* 其中差异图会用绿色标出差异的部分。*/set3ImageTo1("", targetImage, baseImage, showDiff(imageDiff, baseImage), "xxxx.jpg" ); imageDiff.release(); baseImage.release(); targetImage.release(); } else { }} /*** 2、截取算法*a、因为图片有通用的顶部bar和底部bar，需要先找到底部bar。*b、截取长图片的部分，然后和底部bar拼接，就完成了图片截取。*c、这里设置一个默认的宽度，然后对比，找到相同部分，就是底部bar。* @return bar的高度*/public static int interceptBarHeight( Mat longImage, Mat shortImage ){ /*** 设置的默认高度。*/int imageSearchMaxHeight = 400; Mat subImageLong = new Mat(longImage, new Rect(0, longImage.size().height() - imageSearchMaxHeight, longImage.size().width(), imageSearchMaxHeight)); Mat subImageShort = new Mat(shortImage, new Rect(0, shortImage.size().height() - imageSearchMaxHeight, shortImage.size().width(), imageSearchMaxHeight)); opencv_core.Mat imageDiff = compareImage(subImageLong,subImageShort); for (int row = imageDiff.size().height() - 1; row > -1; row--) {for (int col = 0; col < imageDiff.size().width(); col++) {BytePointer bytePointer = imageDiff.ptr(row, col); if (bytePointer.get(0) != 0) {imageDiff.release(); return imageSearchMaxHeight-row; }}}return imageSearchMaxHeight; } /*** 这里将两张图片作为参数传入，* 获取到共同的底部之后。对长图进行截取，* 然后将顶部和底部拼接在一起就ok了。* @param longImage* @param shortImage* @return*/public static opencv_core.Mat dealLongImage( Mat longImage, Mat shortImage ){ int diffHeight = longImage.size().height()-shortImage.size().height(); int barHeight = interceptBarHeight(longImage,shortImage); opencv_core.Mat dealedLongImage = new Mat(longImage,new Rect(0,0,longImage.size().width(),shortImage.size().height()-barHeight) ); opencv_core.Mat imageBar = new Mat(longImage,new Rect(0,longImage.size().height()-barHeight,longImage.size().width(),barHeight) ); opencv_core.Mat dealedLongImageNew = dealedLongImage.clone(); /*** 将头部和底部bar拼接在一起。*/vconcat(dealedLongImage, imageBar, dealedLongImageNew); imageBar.release(); dealedLongImage.release(); return dealedLongImageNew; } public static opencv_core.Mat compareImage( opencv_core.Mat targetImage, opencv_core.Mat baseImage ){ opencv_core.Mat targetImageClone = targetImage.clone(); opencv_core.Mat baseImageColne = baseImage.clone(); opencv_core.Mat imgDiff1 = targetImage.clone(); opencv_core.Mat imgDiff = targetImage.clone(); /*** 首先将图片转成灰度图，*/cvtColor(targetImage, targetImageClone, COLOR_BGR2GRAY); cvtColor(baseImage, baseImageColne, COLOR_BGR2GRAY); /*** 两个矩阵相减，获得差异图。*/subtract(targetImageClone, baseImageColne, imgDiff1); subtract(baseImageColne, targetImageClone, imgDiff); /*** 按比重进行叠加。*/addWeighted(imgDiff, 1, imgDiff1, 1, 0, imgDiff); /*** 图片二值化，大于24的为1，小于24的为0*/threshold(imgDiff, imgDiff, 24, 255, THRESH_BINARY); erode(imgDiff, imgDiff, new opencv_core.Mat()); dilate(imgDiff, imgDiff, new opencv_core.Mat()); return imgDiff; } private static void set3ImageTo1(String logTag, Mat imageSrc, Mat imageBaseSrc, Mat imageDest, String mergePicResult ) { if (imageSrc.size().width() == imageDest.size().width() && imageBaseSrc.size().height() == imageDest.size().height()) {Mat img = imageSrc.clone(); Mat imgBase = imageBaseSrc.clone(); Mat imgDest = imageDest.clone(); Mat imgLine = new Mat(imgBase.size().height(), 1, CV_8UC3, new Scalar(0, 0, 0, 255)); Mat largeImg2 = new Mat(); Mat largeImg3 = new Mat(); Mat largeImg4 = new Mat(); Mat largeImg5 = new Mat(); /*** 横向拼接。*/hconcat(img, imgLine, largeImg2); hconcat(largeImg2, imgBase, largeImg3); hconcat(largeImg3, imgLine, largeImg4); hconcat(largeImg4, imgDest, largeImg5); imwrite( mergePicResult, largeImg5); img.release(); imgBase.release(); imgDest.release(); imgLine.release(); largeImg2.release(); largeImg3.release(); largeImg4.release(); largeImg5.release(); } else {Log.info(logTag+" pictures merge failed"); imwrite( mergePicResult, imageDest); } } private static Mat showDiff(Mat imgDiff, Mat imgBase) { MatVector rgbFrame = new MatVector(); Mat imgDest = imgBase.clone(); split(imgBase, rgbFrame); subtract(rgbFrame.get(2), imgDiff, rgbFrame.get(2)); subtract(rgbFrame.get(0), imgDiff, rgbFrame.get(0)); addWeighted(rgbFrame.get(1), 1, imgDiff, 1, 0, rgbFrame.get(1)); merge(rgbFrame, imgDest); return imgDest; } public static void main( String[] args ){ String targetImageUrl = "2022-03-15-11-37-35-2ouA9yi9gjsGWHDAoaZTaNe4awr0xSlohFq0gF0m.png"; String baseImageUrl = "2022-03-15-11-37-38-njH2kVzd3boX1i8q8bLCfnnIj8xTLyHhHufgs9rp.png"; compareImage(targetImageUrl,baseImageUrl); } }

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