从图像中删除背景并仅拍摄图像部分以便在iOS中保存

CGFloat colorMasking[6]={222,255,222,255};
CGImageRef imageRef = CGImageCreateWithMaskingColors([IMG CGImage],colorMasking);
UIImage  *resultThumbImage = [UIImage imageWithCGImage:imageRef scale:ThumbImage.scale orientation:IMG.imageOrientation];

通常,根据经验,背景颜色与所有其他颜色的差异越大,
将图像分割成前景和后景更容易.在这种情况下,就像@Chris一样
建议,可以使用简单的色度键实现.以下是我的快速
在 Wikipedia上描述的键控的实现(它用C语言编写但是将其翻译成
Objective-C应该很简单)：

/**
 * @brief Separate foreground from background using simple chroma keying.
 *
 * @param imageBGR   Image with monochrome background
 * @param chromaBGR  Color of the background (using channel order BGR and range [0,255])
 * @param tInner     Inner threshold,color distances below this value will be counted as foreground
 * @param tOuter     Outer threshold,color distances above this value will be counted as background
 *
 * @return  Mask (0 - background,255 - foreground,[1,255] - partially fore- and background)
 *
 * Details can be found on [Wikipedia][1].
 *
 * [1]: https://en.wikipedia.org/wiki/Chroma_key#Programming
 */
cv::Mat1b chromaKey( const cv::Mat3b & imageBGR,cv::Scalar chromaBGR,double tInner,double tOuter )
{
    // Basic outline:
    //
    // 1. Convert the image to YCrCb.
    // 2. Measure Euclidean distances of color in YCrBr to chroma value.
    // 3. Categorize pixels:
    //   * color distances below inner threshold count as foreground; mask value = 0
    //   * color distances above outer threshold count as background; mask value = 255
    //   * color distances between inner and outer threshold a linearly interpolated; mask value = [0,255]

    assert( tInner <= tOuter );

    // Convert to YCrCb.
    assert( ! imageBGR.empty() );
    cv::Size imageSize = imageBGR.size();
    cv::Mat3b imageYCrCb;
    cv::cvtColor( imageBGR,imageYCrCb,cv::COLOR_BGR2YCrCb );
    cv::Scalar chromaYCrCb = bgr2ycrcb( chromaBGR ); // Convert a single BGR value to YCrCb.

    // Build the mask.
    cv::Mat1b mask = cv::Mat1b::zeros( imageSize );
    const cv::Vec3d key( chromaYCrCb[ 0 ],chromaYCrCb[ 1 ],chromaYCrCb[ 2 ] );

    for ( int y = 0; y < imageSize.height; ++y )
    {
        for ( int x = 0; x < imageSize.width; ++x )
        {
            const cv::Vec3d color( imageYCrCb( y,x )[ 0 ],imageYCrCb( y,x )[ 1 ],x )[ 2 ] );
            double distance = cv::norm( key - color );

            if ( distance < tInner )
            {
                // Current pixel is fully part of the background.
                mask( y,x ) = 0;
            }
            else if ( distance > tOuter )
            {
                // Current pixel is fully part of the foreground.
                mask( y,x ) = 255;
            }
            else
            {
                // Current pixel is partially part both,fore- and background; interpolate linearly.
                // Compute the interpolation factor and clip its value to the range [0,255].
                double d1 = distance - tInner;
                double d2 = tOuter   - tInner;
                uint8_t alpha = static_cast< uint8_t >( 255. * ( d1 / d2 ) );

                mask( y,x ) = alpha;
            }
        }
    }

    return mask;
}

可以在此Github Gist中找到完整的代码示例.

不幸的是,你的例子不遵循这个经验法则.自从前景和
背景仅在强度上变化,难以(或甚至不可能)找到单个全局集
良好分离的参数：

>物体周围的黑线但物体内没有孔(tInner = 50,tOuter = 90)

>物体周围没有黑线,物体内部没有孔(tInner = 100,tOuter = 170)

因此,如果您无法更改图像的背景
需要复杂的方法.但是,快速简单的示例实现有点超出范围,但您可能需要查看image segmentation和image segmentation的相关区域
alpha matting.