I want to create an image matching application. When I searched for it, I found two good approaches.
1) LIRE - Lucene Image Retrieval can be used to perform the image matching , where it implements various image matching algorithms and and also indexes feature descriptors which can be used later to be matched against the query image.
2) GLCM - Gray Scale Co-occurance Matrix, where the features of a gray scale image is stored in the form of a matrix called the Co-occurrence matrix, and when an image has to be matched, then the matrix of the given image is calculated and important features are matched to calculate the similarity.
Both these approaches seem scalable and fast. But I am not able to decide which might perform better. So any help regarding this or the situations during which they are an advantage is what I am looking for.