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PODFT to spatial domain in OpenCV is not working
 

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  1. PODFT to spatial domain in OpenCV is not working
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    <p>I have created dft of an image and after some adjustment with filters i want to convert it back to the real image but every time when i do that it gives me wrong result ..seems like its not converting it back. <code>ForierTransform</code> and <code>createGaussianHighPassFilter</code> are my own functions rest of the code i am using like below for the inversion back to real image.</p> <pre><code>Mat fft = ForierTransform(HeightPadded,WidthPadded); Mat ghpf = createGaussianHighPassFilter(Size(WidthPadded, HeightPadded), db); Mat res; cv::multiply(fft,ghpf,res); imshow("fftXhighpass1", res); idft(res,res,DFT_INVERSE,res.rows); cv::Mat croped = res(cv::Rect(0, 0, img.cols,img.rows)); //res.convertTo(res,CV_32S); imshow("fftXhighpass", res); </code></pre> <p>even if i dont apply the filter i am unable to reverse back dft result ... here is my dft code is , i could not find any sample to reverse dft back to normal image..</p> <pre><code>Mat ForierTransform(int M,int N) { Mat img = imread("thumb1-small-test.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat padded; copyMakeBorder(img, padded, 0, M - img.rows, 0, N - img.cols, BORDER_CONSTANT, Scalar::all(0)); Mat planes[] = {Mat_&lt;float&gt;(padded), Mat::zeros(padded.size(), CV_32F)}; Mat complexImg; merge(planes, 2, complexImg); dft(complexImg, complexImg); split(complexImg, planes); magnitude(planes[0], planes[1], planes[0]); Mat mag = planes[0]; mag += Scalar::all(1); log(mag, mag); // crop the spectrum, if it has an odd number of rows or columns mag = mag(Rect(0, 0, mag.cols &amp; -2, mag.rows &amp; -2)); normalize(mag, mag, 0, 1, CV_MINMAX); return mag; } </code></pre> <p>kindly help</p> <p>[EDIT: After I found the solution with the help of mevatron] (below is the correct code)</p> <pre><code> Mat ForierTransform(int M,int N) { Mat img = imread("thumb1-small-test.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat padded; copyMakeBorder(img, padded, 0, M - img.rows, 0, N - img.cols, BORDER_CONSTANT, Scalar::all(0)); Mat planes[] = {Mat_&lt;float&gt;(padded), Mat::zeros(padded.size(), CV_32F)}; Mat complexImg; merge(planes, 2, complexImg); dft(complexImg, complexImg); return complexImg; } Mat img = imread("thumb1-small-test.jpg",CV_LOAD_IMAGE_GRAYSCALE); int WidthPadded=0,HeightPadded=0; WidthPadded=img.cols*2; HeightPadded=img.rows*2; int M = getOptimalDFTSize( img.rows ); //Create a Gaussian Highpass filter 5% the height of the Fourier transform double db = 0.05 * HeightPadded; Mat fft = ForierTransform(HeightPadded,WidthPadded); Mat ghpf = createGaussianHighPassFilter(Size(WidthPadded, HeightPadded), db); Mat res; cv::mulSpectrums(fft,ghpf,res,DFT_COMPLEX_OUTPUT); idft(res,res,DFT_COMPLEX_OUTPUT,img.rows); Mat padded; copyMakeBorder(img, padded, 0, img.rows, 0, img.cols, BORDER_CONSTANT, Scalar::all(0)); Mat planes[] = {Mat_&lt;float&gt;(padded), Mat::zeros(padded.size(), CV_32F)}; split(res, planes); magnitude(planes[0], planes[1], planes[0]); Mat mag = planes[0]; mag += Scalar::all(1); log(mag, mag); // crop the spectrum, if it has an odd number of rows or columns mag = mag(Rect(0, 0, mag.cols &amp; -2, mag.rows &amp; -2)); int cx = mag.cols/2; int cy = mag.rows/2; normalize(mag, mag, 1, 0, CV_MINMAX); cv::Mat croped = mag(cv::Rect(cx, cy, img.cols,img.rows)); cv::threshold(croped , croped , 0.56, 1, cv::THRESH_BINARY); imshow("fftPLUShpf", mag); imshow("cropedBinary", croped); </code></pre> <p>It now can able to display ridges valley of finger , and can be more optimize with respect to threshold as well</p>
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    1. COguys please help me out from this ....i have tried some tests by changing the code in ForierTransform function i have returned the planes element 1 like below. Doing this get me the real pic but it is very large faint and with very bad look.. I have just returned the Planes[1] instead of further below calculation of ForierTransform(int M,int N) function. e.g. after magnitude(planes[0], planes[1], planes[0]); return planes[1];
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    2. COon the conversion side i have added few more code idft(res,res,DFT_INVERSE + DFT_SCALE,img.rows); Mat padded; copyMakeBorder(img, padded, 0, img.rows, 0, img.cols, BORDER_CONSTANT, Scalar::all(0)); Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)}; split(res, planes); magnitude(planes[0], planes[1], planes[0]); Mat mag = planes[0]; mag += Scalar::all(1); log(mag, mag); mag = mag(Rect(0, 0, mag.cols & -2, mag.rows & -2)); normalize(mag, mag, 1, 0, CV_MINMAX);
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    3. COthe result comes like this http://oi40.tinypic.com/jshvdu.jpg kindly help me , i have spent several hours and still no success....
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