Improved image retrieval using color-invariant moments

Content-based image retrieval (CBIR) is growing research field in computer vision in which, we retrieve images that are visually relevant to the query. As we know that, CBIR system requires low-level descriptors, and many different methods have been recently proposed using color, texture, and shape based descriptors. Some of these methods use the histogram or some variation for representing color which may require a significant amount of similarity calculation and space. This paper uses L2 similarity measure on small dimension of hybrid color and shape features. i.e include Euclidean distance as L2 measure, color moment as color feature and invariant moment as a shape feature. From the descriptive analysis on benchmark Wang database, it is observed that proposed hybrid feature with L2 similarity measure performed significantly encouraging. For 20 number of retrieved images, it gives 66.2% mean-average precision and 13.24 % mean-average recall.