Effects of Different Gabor Filter Parameters on Image Retrieval by Texture
MMM '04 Proceedings of the 10th International Multimedia Modelling Conference
An Interactive Image Feature Visualization System for Supporting CBIR Study
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
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A key issue of content-based image retrieval is exploring how to bridge the gap between the high-level semantics of an image and its lower-level properties, such as color, texture and edge. In this paper, we present a new method using perceptual edge features, called generic edge tokens (GET), as image shape content descriptors for CBIR. GETs represent basic types of perceptually distinguishable edge segments including both linear and nonlinear features, which are modeled as qualitative shape descriptors based on perceptual organization principles. In the method, an image is first transformed into GET map on the fly. The base GETs can be grouped into higher-level perceptual shape structures (PSS) as additional shape descriptors. Image content is represented statistically by perceptual feature histograms (PFHs) of GETs and PSSs. Similarity is evaluated by comparing the differences between the corresponding PFHs from two images. Experimental results are provided to demonstrate the potential of the proposed method.