Image retrieval using blob histograms

We present a new method for image indexing and retrieval that is based on pixel statistics from varying spatial scales. The proposed method employs a structuring element to determine the frequency distribution of pixels locally in the image and to detect local groups of pixels with uniform color or texture attributes. The frequency distribution and relative sizes of such groups are summarized into a table termed as a blob histogram. By embedding spatial information, color blob histograms are able to distinguish images that have the same color pixel distribution but contain objects with different sizes or shapes, without the need for segmentation. Using isotropic structuring elements, blob histograms are invariant to rotations and translations of the objects in an image. Experimental results of using blob histograms in image retrieval are given in the paper.