FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Human-inspired order-based block feature in the HSI color space for image retrieval
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
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CBIR makes a wide use of histogram based methods for image indexing. Histograms describe the global intensity distribution of images. They are very easy to compute and are insensitive to small changes in object translations and rotations. However, they are not robust to large appearance changes, and they might give similar results for different kinds of images if the distributions of colors are same in the images. Our research focuses mainly on the image bins (histogram value divisions by frequency) separation technique followed by calculating the sum of values, and using them as image local features. At first, the histogram is first calculated for an image. After that, it is subdivided into sixteen equal bins and the sum of local values is calculated and stored. We have tested the proposed algorithm on a large database of images.