i am using SIFT algorithm in matlab to determine the similarity between template image and a set of images, where in the end i have to determine the best match between set of images on the basis of SCORES,is it true to say that higher the score of an image the better the match? i am aware that when there is an exact match, the score is zero, but what if the image is similar?
I assume by SCORES you mean a similarity measurement between a pair of matched descriptors (e.g. euclidean distance). If my assumption is correct, statistically averaging the scores of all matches (e.g. SSD) should give you a degree of similarity between the two images. I.e., the smaller the averaged scores, the higher the similarity, zero meaning perfect match. To improve this similarity metric you can have a look at RANSAC which is able to remove outliers in your set of matched descriptors.
EDIT: Averaging the match scores is of course only meaningful if the percentage of matched descriptors is sufficiently high (as Maurits suggests). So a combination of counting matches and averaging distances might be a reasonable approach.