Scene Retrieval of Natural Images
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Structured-image retrieval invariant to rotation, scaling and translation
WSEAS TRANSACTIONS on SYSTEMS
An effective image retrieval scheme using color, texture and shape features
Computer Standards & Interfaces
Content based image retrieval using combined features
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Content-based image retrieval using color and texture fused features
Mathematical and Computer Modelling: An International Journal
Self organizing natural scene image retrieval
Expert Systems with Applications: An International Journal
A new content-based image retrieval technique using color and texture information
Computers and Electrical Engineering
Spatial weighting for bag-of-features based image retrieval
IUKM'13 Proceedings of the 2013 international conference on Integrated Uncertainty in Knowledge Modelling and Decision Making
Engineering Applications of Artificial Intelligence
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Color, texture and shape information have been the primitive image descriptors in content based image retrieval systems. This paper presents a novel framework for combining all the three i.e. color, texture and shape information, and achieve higher retrieval efficiency. The image is partitioned into non- overlapping tiles of equal size. The color moments and moments on gabor filter responses of these tiles serve as local descriptors of color and texture respectively. This local information is captured for two resolutions and two grid layouts that provide different details of the same image. An integrated matching scheme, based on most similar highest priority (MSHP) principle and the adjacency matrix of a bipartite graph formed using the tiles of query and target image, is provided for matching the images. Shape information is captured in terms of edge images computed using Gradient Vector Flow fields. Invariant moments are then used to record the shape features. The combination of the color, texture and shape features provide a robust feature set for image retrieval. The experimental results demonstrate the efficacy of the method. KEY WORDS Multiresolution grid, Integrated matching, Local descriptors, Gradient vector flow field.