In this study, a novel technique for image retrieval based on selective
regions matching using region codes is presented. All images in the
database are uniformly divided into multiple regions and each region is
assigned a 4-bit region code based upon its location relative to the
central region. Dominant color and Local Binary Pattern (LBP) based texture
features are extracted from these regions. Feature vectors together with
their region codes are stored and indexed in the database. During
retrieval, feature vectors of regions having region codes similar to the
query image region are used for comparison. To reflect the user's intent in
query formulation in a better way, an effective technique for Region of
Interest (ROI) overlapping block selection is also proposed. Region codes
are further used to find relative locations of multiple ROIs in query and
target images. The performance of the proposed approach is tested on the
MPEG-7 CCD database and Corel image database. Experimental results show
that the proposed approach increases the accuracy and reduces image
retrieval time.
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