Feature extraction for classification
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Hi there, I attached the images that I want to extract features for classification. these are zoomed images of different fruits. kindly help me how to find features on these images. I tried using extractHOGfeatures function but its not giving me correct classification.
2 个评论
Image Analyst
2017-9-20
What are the classes? How many classes are in each photo? One? If so, then one feature may simply be the color. Why do you think HOG should be what you want? Can you attach what you think the classification should look like?
Ushna Asif
2017-9-21
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Image Analyst
2017-9-21
0 个投票
I would think that just color (Hue and Saturation) and texture might be enough. Of course if two images look the same but are different fruits, there is no telling, like you have an image of orange grainy things and one is an apricot and one is a nectarine.
3 个评论
Ushna Asif
2017-9-21
Image Analyst
2017-9-21
I have examples in my File Exchange: http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862&sort=downloads_desc
For example, convert to HSV color space and get the mean hue, saturation, and value.
hsvImage = rgb2hsv(rgbImage);
meanHue = mean2(hsvImage(:,:,1))
meanSat = mean2(hsvImage(:,:,2))
meanValue = mean2(hsvImage(:,:,3))
sdImage = stdfilt(hsvImage(:,:,3)); % Std Deviation of Value channel.
meanStdDev = mean2(sdImage);
You can make a feature vector for this one image like
featureVector = [meanHue, meanSat, meanValue, meanStdDev];
Ushna Asif
2017-9-22
更多回答（1 个）
Akira Agata
2017-9-21
0 个投票
I believe the following example will be your help. Using this method, you can extract 4096-dimensional feature vector for each image.
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