this is the input image i want to detect scratches in this image but i don't know how to proceed please guide me. i want output image like this

2 Kommentare

Walter Roberson
Walter Roberson am 20 Nov. 2015
You appear to have marked blobs, not scratches. Scratches are long thin marks such as appear near the bottom left of the bright area.
mehroz irshad
mehroz irshad am 20 Nov. 2015
so how can i detect those blobs.

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Antworten (1)

Image Analyst
Image Analyst am 20 Nov. 2015

0 Stimmen

Try a tophat or bottomhat filter, imtophat() or imbothat().

3 Kommentare

mehroz irshad
mehroz irshad am 20 Nov. 2015
Bearbeitet: Walter Roberson am 20 Nov. 2015
original = imread('fivTest.png');
figure, imshow(original);
se = strel('disk',12);
tophatFiltered = imtophat(original,se);
figure, imshow(tophatFiltered);
contrastAdjusted = imadjust(tophatFiltered);
figure, imshow(contrastAdjusted);
i have tried this code tophat filter but displays following error.
Error using images.internal.imageDisplayValidateParams>validateCData (line 119)
If input is logical (binary), it must be two-dimensional.
Error in images.internal.imageDisplayValidateParams (line 27)
common_args.CData = validateCData(common_args.CData,image_type);
Error in images.internal.imageDisplayParseInputs (line 78)
common_args = images.internal.imageDisplayValidateParams(common_args);
Error in imshow (line 222)
images.internal.imageDisplayParseInputs({'Parent','Border','Reduce'},preparsed_varargin{:});
Error using imadjust>parseInputs (line 207)
Specified syntax IMADJUST(I) is only supported for 2-D grayscale images. Additional input arguments are required for use
with RGB images.
Error in imadjust (line 97)
parseInputs(varargin{:});
original = rgb2gray( imread('fivTest.png') );
Image Analyst
Image Analyst am 20 Nov. 2015
You should also get a better photo. Your setup is horrible. Have you considered using more uniform illumination, board illumination (no line or point sources of light), crossed polarizers (to knock out that specular reflections right where you want to analyze), etc. It's always better to start with a good image than to try to fix us a crappy image afterwards in software.

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am 19 Nov. 2015

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am 20 Nov. 2015

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