Well the question is simple i want to find similar images given a query image, similar to what TinEye does. Suppose I have a shirt with the following description
Sleeve length : full
collar : present
pattern : striped
(The above data is just to give you a feel of image i actually dont have this data)
First image is the query image and the next should be the output of the similarity finding algorithm. So based on the example we have a flexibility like we can show the user an image with a changed color, we can see all the images have the same pattern, the same collar type or sleeve length. So i have to show the output which are visually similar.
There are similar thread on stack also¬†link from stack¬†and not only this but there are many other. But i am confused about the approach to follow.
In my case i dont have to search in another category I have to search in the same category like if the input is shirt i will search in the shirt category only. That part has been done.
So the question is what are the approaches to handle this problem. for the color it is no big issue. Color information can be easily extracted through color histogram. Lets say the input is TShirt round neck i.e. without collar, half sleeve and printed at center with text. Now the output should be images similar to those like half sleeve, round collar, and printed text at center. thought the text may vary. I tried K-Means clustering and P-hash but that didnt work. Please enlighten me
PS : I have to find similar images not duplicates.