ios - Detection of sharpness of a photo -

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i'm looking framework helps detecting sharpness of photo. have read this post points methodology of doing so. i'd rather work library getting hands dirty.

in documentation of core image apple says:

core image can analyze quality of image , provide set of filters optimal settings adjusting such things hue, contrast, , tone color, , correcting flash artifacts such red eye. 1 method call on part.

how can 'analyze image quality' part? i'd love see example code.

we did gpuimage framework (calculate brightness , sharpness): (here snippets might you) 

-(bool) calculatebrightness:(uiimage *) image { float result  = 0; int = 0; (int y = 0; y < image.size.height; y++) {     (int x = 0; x < image.size.width; x++) {         uicolor *color = [self colorat:image                                    atx:x                                   andy:y];         const cgfloat * colors = cgcolorgetcomponents(color.cgcolor);         float r = colors[0];         float g = colors[1];         float b = colors[2];         result += .299 * r + 0.587 * g + 0.114 * b;         i++;     } } float brightness = result / (float)i; nslog(@"image brightness : %f",brightness); if (brightness > 0.8 || brightness < 0.3) {     return no; } return yes;

}

-(bool) calculatesharpness:(uiimage *) image { gpuimagecannyedgedetectionfilter *filter = [[gpuimagecannyedgedetectionfilter alloc] init]; binaryimagedistancetransform *binimagtrans = [[binaryimagedistancetransform alloc] init ]; nsarray *resultarray = [binimagtrans twodimdistancetransform:[self getbinaryimageasarray:[filter imagebyfilteringimage:image]]];  if (resultarray == nil) {     return no; }  int sum = 0; (int x = 0; x < resultarray.count; x++) {     nsmutablearray *col = resultarray[x];     sum += (int)[col valueforkeypath:@"@max.intvalue"]; }  // values under analysis nslog(@"image sharp : %i",sum); if (sum < 26250000) { // tested - bad sharpness under ca. 26250000     return no; } return yes;

}

but slow. takes ca. 40 seconds 1 image ipad camera.


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