How to provide a score to an image based on pattern information in it?
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Hello,
I am very new to image segmentation and pattern recognition. I have been reading quite a lot of literature and tried different functions available in MATLAB to find out patterns in the input image. I tried using Color-Based Segmentation Using K-Means Clustering, applied the Image segmentation tutorial and some other functionalities. These work well in segmenting the image and giving me details on the number of pixels, mean intensity of regions, etc. I was wondering if there is something like a numeric score which can be assigned to an image which contains more patterns in it (I tried using entropy as a score but it does not provide me a satisfactory measure to rank multiple images based on the amount of information in the image). Any information about already available functions/literature in the direction would be very helpful for me to proceed. Here are the images which I am using, and would like provide each image a numeric score based on the amount of information (patterns) they contain.
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Image Analyst
on 17 Feb 2016
There are a nearly infinite number of patterns in every image. Any grouping of pixels could be considered as its own pattern. You're going to have to be more specific as to what you would like the score to represent. How about the area fraction of pixels brighter than a certain threshold? How about the mean gray level of pixels brighter than a certain threshold? How about the standard deviation of pixels brighter than a certain threshold? We don't know what you want or what would be useful to you.
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Image Analyst
on 17 Feb 2016
You just have to decide how bright is bright enough to be considered. Maybe it's everything with a gray level of 0 and up, or maybe it's 1 and up. Or maybe 50 and up. I don't know how dark things get in your image and what should be ignored or paid attention to.
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