Local versus Global Features for Content-Based Image Retrieval
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Efficient region-based image retrieval
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Content Based Image Retrieval Using Color, Texture and Shape Features
ADCOM '07 Proceedings of the 15th International Conference on Advanced Computing and Communications
CTex—An Adaptive Unsupervised Segmentation Algorithm Based on Color-Texture Coherence
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper a novel approach for image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. For color the histogram of images are computed, for texture co-occurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, an idea is based on greedy strategy to reduce the computational complexity. The entire system will be developed using MALAB (an open source product), The system will be tested with Image database containing 1000 natural images.