Texture discrimination by Gabor functions
Biological Cybernetics
Identifying high level features of texture perception
CVGIP: Graphical Models and Image Processing
Periodicity, Directionality, and Randomness: Wold Features for Image Modeling and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
A High Fidelity Contrast Improving Model Based on Human Vision Mechanisms
ICMCS '99 Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
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We have been researching on modeling of visual cognition and its application to content-based image retrievel. We started with analyzing the relationship between pre-attentive vision and attentive vision. And we focused on human early vision as pre-attentive vision. We selected statistical texture images as targets because attentive vision was hard to act them. Previously, many texture features have been proposed, but most of them were insufficient to account for human subjectivity. And so, we have newly designed texture features which were adequate to account for human subjectivity. From the viewpoint of physiological fundamentals and psychological review, we have focused on the orientation feature and color feature of an image, and calculating contrast of these features in various resolutions. Next, we have measured psychological responses by using some descriptive adjectives, and corresponded them to our texture features by adopting the canonical correlation statistics. Based on this correspondence, we developed a contrast based subjective texture image retrievel (CBSTIR) system. Our system can retrieve images which give a similar impression, and also predict images by some descriptive adjectives. From the experimental results, we found that approximate color property was significant to subjective retrievel, while the precise color distribution was significant to non-subjective retrieval. Moreover, we found that the global orientation interaction in multi resolutions was significatn to subjective retrieval.