最近要實作人像扣圖的功能，我在網上查到的扣圖的方式主要有兩種，一種是coreImage 色域,一種是openCv邊緣檢測 第一種适合純色背景，扣圖精準，第二種，适合複雜背景，但是預設的扣圖不精确，如下圖 1.處理前的照片
2.處理後的照片
coreImage 網上已經有很多實作了，也有很多文章，我就不多說了，我隻把我實作的代碼貼出來，代碼粘過去就能用，另忘了，導入CubeMap.c
//coreImage 扣圖 createCubeMap（值1，值2）值範圍0～360 扣掉值1到值2範圍内的顔色
CubeMap myCube = createCubeMap(self.slider1.value, self.slider2.value);
NSData *myData = [[NSData alloc]initWithBytesNoCopy:myCube.data length:myCube.length freeWhenDone:true];
CIFilter *colorCubeFilter = [CIFilter filterWithName:@"CIColorCube"];
[colorCubeFilter setValue:[NSNumber numberWithFloat:myCube.dimension] forKey:@"inputCubeDimension"];
[colorCubeFilter setValue:myData forKey:@"inputCubeData"];
[colorCubeFilter setValue:[CIImage imageWithCGImage:_preview.image.CGImage] forKey:kCIInputImageKey];
CIImage *outputImage = colorCubeFilter.outputImage;
CIFilter *sourceOverCompositingFilter = [CIFilter filterWithName:@"CISourceOverCompositing"];
[sourceOverCompositingFilter setValue:outputImage forKey:kCIInputImageKey];
[sourceOverCompositingFilter setValue:[CIImage imageWithCGImage:backgroundImage.CGImage] forKey:kCIInputBackgroundImageKey];
outputImage = sourceOverCompositingFilter.outputImage;
CGImage *cgImage = [[CIContext contextWithOptions: nil]createCGImage:outputImage fromRect:outputImage.extent];
下面我講一下，ios結合openCv實作扣圖的方法
下載下傳opencv2 具體怎麼IOS下弄opencv 請見我之前寫的一貼部落格： http://blog.csdn.net/wuzehai02/article/details/8439778
IOS使用OPENCV實作物體跟蹤
頭檔案導入下面幾個
#import <opencv2/opencv.hpp>
#import "UIImage+OpenCV.h"
UIImage+OpenCV類
//
// UIImage+OpenCV.h
#import <UIKit/UIKit.h>
#import <opencv2/opencv.hpp>
@interface UIImage (UIImage_OpenCV)
+(UIImage *)imageWithCVMat:(constcv::Mat&)cvMat;
-(id)initWithCVMat:(constcv::Mat&)cvMat;
@property(nonatomic,readonly) cv::Mat CVMat;
@property(nonatomic,readonly) cv::Mat CVGrayscaleMat;
@end
//
// UIImage+OpenCV.mm
#import "UIImage+OpenCV.h"
staticvoid ProviderReleaseDataNOP(void *info,const void *data,size_t size)
{
// Do not release memory
return;
}
@implementation UIImage (UIImage_OpenCV)
-(cv::Mat)CVMat
{
CGColorSpaceRef colorSpace =CGImageGetColorSpace(self.CGImage);
CGFloat cols =self.size.width;
CGFloat rows =self.size.height;
cv::Mat cvMat(rows, cols,CV_8UC4); // 8 bits per component, 4 channels
CGContextRef contextRef = CGBitmapContextCreate(cvMat.data, // Pointer to backing data
cols, // Width of bitmap
rows, // Height of bitmap
8, // Bits per component
cvMat.step[0], // Bytes per row
colorSpace, // Colorspace
kCGImageAlphaNoneSkipLast |
kCGBitmapByteOrderDefault); // Bitmap info flags
CGContextDrawImage(contextRef, CGRectMake(0, 0, cols, rows), self.CGImage);
CGContextRelease(contextRef);
return cvMat;
}
-(cv::Mat)CVGrayscaleMat
{
CGColorSpaceRef colorSpace =CGColorSpaceCreateDeviceGray();
CGFloat cols =self.size.width;
CGFloat rows =self.size.height;
cv::Mat cvMat =cv::Mat(rows, cols,CV_8UC1); // 8 bits per component, 1 channel
CGContextRef contextRef = CGBitmapContextCreate(cvMat.data, // Pointer to backing data
cols, // Width of bitmap
rows, // Height of bitmap
8, // Bits per component
cvMat.step[0], // Bytes per row
colorSpace, // Colorspace
kCGImageAlphaNone |
kCGBitmapByteOrderDefault); // Bitmap info flags
CGContextDrawImage(contextRef, CGRectMake(0, 0, cols, rows), self.CGImage);
CGContextRelease(contextRef);
CGColorSpaceRelease(colorSpace);
return cvMat;
}
+ (UIImage *)imageWithCVMat:(constcv::Mat&)cvMat
{
return [[[UIImagealloc] initWithCVMat:cvMat]autorelease];
}
- (id)initWithCVMat:(constcv::Mat&)cvMat
{
NSData *data = [NSDatadataWithBytes:cvMat.datalength:cvMat.elemSize() * cvMat.total()];
CGColorSpaceRef colorSpace;
if (cvMat.elemSize() == 1)
{
colorSpace = CGColorSpaceCreateDeviceGray();
}
else
{
colorSpace = CGColorSpaceCreateDeviceRGB();
}
CGDataProviderRef provider =CGDataProviderCreateWithCFData((CFDataRef)data);
CGImageRef imageRef = CGImageCreate(cvMat.cols, // Width
cvMat.rows, // Height
8, // Bits per component
8 * cvMat.elemSize(), // Bits per pixel
cvMat.step[0], // Bytes per row
colorSpace, // Colorspace
kCGImageAlphaNone | kCGBitmapByteOrderDefault, // Bitmap info flags
provider, // CGDataProviderRef
NULL, // Decode
false, // Should interpolate
kCGRenderingIntentDefault); // Intent
self = [selfinitWithCGImage:imageRef];
CGImageRelease(imageRef);
CGDataProviderRelease(provider);
CGColorSpaceRelease(colorSpace);
return self;
}
@end
好了，上面的都是準備工作，具體的代碼其實很簡單
cv::Mat grayFrame,_lastFrame, mask,bgModel,fgModel;
_lastFrame = [self.preview.imageCVMat];
cv::cvtColor(_lastFrame, grayFrame,cv::COLOR_RGBA2BGR);//轉換成三通道bgr
cv::Rect rectangle(1,1,grayFrame.cols-2,grayFrame.rows -2);//檢測的範圍
//分割圖像
cv::grabCut(grayFrame, mask, rectangle, bgModel, fgModel, 3,cv::GC_INIT_WITH_RECT);//openCv強大的扣圖功能
int nrow = grayFrame.rows;
int ncol = grayFrame.cols * grayFrame.channels();
for(int j=0; j<nrow; j++){//扣圖，不知道這樣寫對不對，我也是新手，請大家多多指教
for(int i=0; i<ncol; i++){
uchar val = mask.at<uchar>(j,i);
if(val==cv::GC_PR_BGD){
grayFrame.at<cv::Vec3b>(j,i)[0]= '\255';
grayFrame.at<cv::Vec3b>(j,i)[1]= '\255';
grayFrame.at<cv::Vec3b>(j,i)[2]= '\255';
}
}
}
cv::cvtColor(grayFrame, grayFrame,cv::COLOR_BGR2RGB); //轉換成彩色圖檔
_preview.image = [[UIImagealloc] initWithCVMat:grayFrame];//顯示結果
上面的代碼測試可用，其實這裡最關鍵的代碼是使用了opencv的grabCut 圖像分割函數
grabCut函數的API說明如下：
void cv::grabCut( InputArray _img, InputOutputArray _mask, Rect rect,
InputOutputArray _bgdModel, InputOutputArray _fgdModel,
int iterCount, int mode )
參考文章：http://blog.csdn.net/zouxy09/article/details/8534954