问题
I am new to machine learning and currently working on a project. The project is about classifying images based on feature and color attributes.
I have tried classifying images through feature extraction based on the example given in the OpenCV with Python by Example book (the Dense extractor SIFT descriptor technique to generate a codebook and train SVM to classify the extracted feature) but I haven't tried yet combining both feature and color attributes since the images sampled were gray-scaled during feature extraction.
My questions are:
- Is the same technique would apply if I include color, that is, I will create a feature map (gray-scaled; shape attribute) and color histogram map and train SVM for both attributes?
- Or is there a way that SIFT can compute both shape and color attributes in OpenCV?
回答1:
I found a project similar to the problem in this paper titled Leveraging Computer Vision Priciples for Image-Based Shoe.
They have utilized different approaches to detect and compare the image color with its shape and texture. I will try their recommended algorithm in opencv and see if this works for the project.. :)
来源：https://stackoverflow.com/questions/35188334/color-and-feature-classification-opencv