Comparing images using color coherence vectors
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Combining supervised learning with color correlograms for content-based image retrieval
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Gabor Wavelet Correlogram Algorithm for Image Indexing and Retrieval
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
An Integrated Color and Intensity Co-occurrence Matrix
Pattern Recognition Letters
Texture image retrieval using rotated wavelet filters
Pattern Recognition Letters
Automated binary texture feature sets for image retrieval
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04
A smart content-based image retrieval system based on color and texture feature
Image and Vision Computing
Expert system for color image retrieval
Expert Systems with Applications: An International Journal
Expert system based on artificial neural networks for content-based image retrieval
Expert Systems with Applications: An International Journal
Series feature aggregation for content-based image retrieval
Computers and Electrical Engineering
Computers and Electrical Engineering
Texture image retrieval using new rotated complex wavelet filters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Rotation-Invariant Texture Image Retrieval Using Rotated Complex Wavelet Filters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Localized discriminative scale invariant feature transform based facial expression recognition
Computers and Electrical Engineering
Fast K-means algorithm based on a level histogram for image retrieval
Expert Systems with Applications: An International Journal
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In this paper, the modified color motif co-occurrence matrix (MCMCM) is presented for content-based image retrieval. The proposed method collects the inter-correlation between the red, green, and blue color planes which is absent in color motif co-occurrence matrix. The proposed method integrates the MCMCM and difference between the pixels of a scan pattern (DBPSP) features with equal weights in contrast to the system which integrates motif co-occurrence matrix, DBPSP, and color histogram with k-mean features with optimized weights. The retrieval results of the proposed method are tested on different image databases i.e. MIT VisTex (DB1) and Corel-1000 (DB2). The results after being investigated show a significant improvement in terms of average retrieval rate and average retrieval precision on DB1 database and average precision, average recall and average retrieval rate on DB2 database as compared to the state-of-art techniques on respective databases.