Nsryjdtyk

i want to equalize two half face color images of the same subject and then merge them. Each of them has different values of hue saturation and brightness....using opencv how can i normalize/equalize each half image?

I tried performing cvEqualizeHist(v, v); on the v value of the converted HSV image, but two images still have significant difference and after the merge still has a line between the colors of the two halves...thanks

Have u tried to read this link? http://answers.opencv.org/question/75510/how-to-make-auto-adjustmentsbrightness-and-contrast-for-image-android-opencv-image-correction/

void Utils::BrightnessAndContrastAuto(const cv::Mat &src, cv::Mat &dst, float clipHistPercent)

{



    CV_Assert(clipHistPercent >= 0);

    CV_Assert((src.type() == CV_8UC1) || (src.type() == CV_8UC3) || (src.type() == CV_8UC4));



    int histSize = 256;

    float alpha, beta;

    double minGray = 0, maxGray = 0;



    //to calculate grayscale histogram

    cv::Mat gray;

    if (src.type() == CV_8UC1) gray = src;

    else if (src.type() == CV_8UC3) cvtColor(src, gray, CV_BGR2GRAY);

    else if (src.type() == CV_8UC4) cvtColor(src, gray, CV_BGRA2GRAY);

    if (clipHistPercent == 0)

    {

        // keep full available range

        cv::minMaxLoc(gray, &minGray, &maxGray);

    }

    else

    {

        cv::Mat hist; //the grayscale histogram



        float range = { 0, 256 };

        const float* histRange = { range };

        bool uniform = true;

        bool accumulate = false;

        calcHist(&gray, 1, 0, cv::Mat(), hist, 1, &histSize, &histRange, uniform, accumulate);



        // calculate cumulative distribution from the histogram

        std::vector<float> accumulator(histSize);

        accumulator[0] = hist.at<float>(0);

        for (int i = 1; i < histSize; i++)

        {

            accumulator[i] = accumulator[i - 1] + hist.at<float>(i);

        }



        // locate points that cuts at required value

        float max = accumulator.back();

        clipHistPercent *= (max / 100.0); //make percent as absolute

        clipHistPercent /= 2.0; // left and right wings

        // locate left cut

        minGray = 0;

        while (accumulator[minGray] < clipHistPercent)

            minGray++;



        // locate right cut

        maxGray = histSize - 1;

        while (accumulator[maxGray] >= (max - clipHistPercent))

            maxGray--;

    }



    // current range

    float inputRange = maxGray - minGray;



    alpha = (histSize - 1) / inputRange;   // alpha expands current range to histsize range

    beta = -minGray * alpha;             // beta shifts current range so that minGray will go to 0



    // Apply brightness and contrast normalization

    // convertTo operates with saurate_cast

    src.convertTo(dst, -1, alpha, beta);



    // restore alpha channel from source 

    if (dst.type() == CV_8UC4)

    {

        int from_to = { 3, 3 };

        cv::mixChannels(&src, 4, &dst, 1, from_to, 1);

    }

    return;

}

I'm not sure as I'm now facing the same problem,
but maybe try to equalize the H & S values instead of the V?

Also try manually adjusting it using Photoshop to see what works best and then try to replicate it using code.