opencv在iOS中的使用［几个滤波］以及uiimage与iplimage互转

<span style="font-family: Arial, Helvetica, sans-serif; background-color: rgb(255, 255, 255);">最近由于项目需要用到美颜，因此初步使用了opencv进行了研究，思路如下：</span>

1 使用滤波，可以采用双边滤波或者高斯滤波；

2 肤色检测；

3 图像的融合，即1和2点融合；

4 锐化增强细节；

但是使用发现opencv不适合移动端的使用，尽量还是采用opengl去做图像处理，利用gpu可以降低cpu使用率；

下面贴出一些我在使用过成中的接口：（参考网上的资料比较多）

特别是uiimage和iplimage互转的时候注意 rotate（

orientation:UIImageOrientationRight

）

// NOTE you SHOULD cvReleaseImage() for the return value when end of the code.
- (IplImage *)CreateIplImageFromUIImage:(UIImage *)image {
CGImageRef imageRef = image.CGImage;

//构造图像
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
IplImage *iplimage = cvCreateImage(cvSize(image.size.width,
image.size.height),
IPL_DEPTH_8U, 4);

CGContextRef contextRef = CGBitmapContextCreate(iplimage->imageData,
iplimage->width,
iplimage->height,
iplimage->depth,
iplimage->widthStep,
colorSpace,
kCGImageAlphaPremultipliedLast|kCGBitmapByteOrderDefault);

CGContextDrawImage(contextRef, CGRectMake(0, 0, image.size.width, image.size.height), imageRef);
CGContextRelease(contextRef);
CGColorSpaceRelease(colorSpace);

IplImage *ret = cvCreateImage(cvGetSize(iplimage), IPL_DEPTH_8U, 3);
cvCvtColor(iplimage, ret, CV_RGBA2BGR);

//ret = cvCloneImage(iplimage);
cvReleaseImage(&iplimage);

return ret;
}

// NOTE You should convert color mode as RGB before passing to this function
- (UIImage *)UIImageFromIplImage:(IplImage *)image {
NSLog(@"IplImage (%d, %d) %d bits by %d channels, %d bytes/row %s", image->width, image->height, image->depth, image->nChannels, image->widthStep, image->channelSeq);

cvCvtColor(image, image, CV_BGR2RGB);

CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
NSData *data = [NSData dataWithBytes:image->imageData length:image->imageSize];
CGDataProviderRef provider = CGDataProviderCreateWithCFData((CFDataRef)data);
CGImageRef imageRef = CGImageCreate(image->width,
image->height,
image->depth,
image->depth * image->nChannels,
image->widthStep,
colorSpace,
kCGImageAlphaNone|kCGBitmapByteOrderDefault,
provider,
NULL,
false,
kCGRenderingIntentDefault);

UIImage *ret = [UIImage imageWithCGImage:imageRef scale:1 orientation:UIImageOrientationRight];

CGImageRelease(imageRef);
CGDataProviderRelease(provider);
CGColorSpaceRelease(colorSpace);
return ret;
}

-(void) process_Histogram:(UIImage *) imageView
{
IplImage *img_color = [self CreateIplImageFromUIImage:imageView];
IplImage* imgChannel[4] = { 0, 0, 0, 0 };
IplImage* dst = cvCreateImage( cvGetSize(img_color), IPL_DEPTH_8U, 3 );

if( img_color )
{
for(int i = 0; i < img_color -> nChannels; i++ )
{
imgChannel[i] = cvCreateImage( cvGetSize( img_color ), IPL_DEPTH_8U, 1 );  //要求单通道图像才能直方图均衡化
}
//通道分离
cvSplit( img_color, imgChannel[0], imgChannel[1], imgChannel[2], imgChannel[3] );//BGRA
for( int i = 0; i < dst -> nChannels; i++ )
{
//直方图均衡化，原始图像和目标图像必须是单通道
cvEqualizeHist( imgChannel[i], imgChannel[i] );
}

//通道组合
cvMerge( imgChannel[0], imgChannel[1], imgChannel[2], imgChannel[3], dst );

m_image = [self UIImageFromIplImage:dst];

//释放资源
for( int i = 0; i < img_color -> nChannels; i++ )
{
if( imgChannel[i] )
{
cvReleaseImage( &imgChannel[i] );
}
}
cvReleaseImage( &dst );
}

}
-(void)process_Image:(UIImage *)imageview
{
IplImage *img_color = [self CreateIplImageFromUIImage:imageview];

IplImage *avgImg = cvCreateImage(cvGetSize(img_color), IPL_DEPTH_8U, img_color->nChannels);
IplImage *medianImg = cvCreateImage(cvGetSize(img_color), IPL_DEPTH_8U, img_color->nChannels);
IplImage *gaussianImg = cvCreateImage(cvGetSize(img_color), IPL_DEPTH_8U, img_color->nChannels);
IplImage *unsharimage = cvCreateImage(cvGetSize(img_color), IPL_DEPTH_8U, img_color->nChannels);

//滤波
//cvSmooth(img_color, avgImg, CV_BLUR,7,img_color->nChannels);  //采用7x7的窗口对图像进行均值滤波

//cvSmooth(img_color, medianImg, CV_MEDIAN, 7, img_color->nChannels);  //采用7x7的窗口对图像进行中值滤波

//cvSmooth(img_color, gaussianImg, CV_BILATERAL ,3 , 3, 100.0, 100.0);  //  双边平滑滤波

cvSmooth(img_color, gaussianImg, CV_GAUSSIAN, 5, 5, 3, 3);  //  Gauss平滑滤波，核大小为7x7

//肤色检测

//图像融合

//锐化
//cvLaplace(gaussianImg, unsharimage);
float low[9] ={ 1.0/16, 2.0/16, 1.0/16, 2.0/16, 4.0/16, 2.0/16, 1.0/16, 2.0/16, 1.0/16 };//低通滤波核
CvMat kernela = cvMat( 3, 3, CV_32FC1, low);

// assigns kernel values

cvFilter2D(gaussianImg, unsharimage, &kernela);

m_image = [self UIImageFromIplImage:unsharimage];

cvReleaseImage(&img_color);
cvReleaseImage(&avgImg);
cvReleaseImage(&medianImg);
cvReleaseImage(&gaussianImg);
}
-(void)process_Gray:(UIImage *)imageview
{
IplImage *img_color = [self CreateIplImageFromUIImage:imageview];
IplImage *pGrayImage = cvCreateImage(cvGetSize(img_color), IPL_DEPTH_8U, 1);
IplImage* grayImagePlus = cvCreateImage(cvGetSize(img_color), IPL_DEPTH_8U, 3);

cvCvtColor(img_color, pGrayImage, CV_BGR2GRAY);//至此grayImage是无法装载到UIImage中的，也是无法在UIImageView显示的，会报错！

//将grayImage的内容再转换回IPL_DEPTH_8U色深、3通道图像
cvCvtColor(pGrayImage, grayImagePlus, CV_GRAY2BGR);//此处将灰度格式图像转换成BGR格式的图像

m_image = [self UIImageFromIplImage:grayImagePlus];

cvReleaseImage(&img_color);
cvReleaseImage(&pGrayImage);
cvReleaseImage(&grayImagePlus);
}