Adaptive Perceptual Color-Texture Image Segmentation

We propose an image segmentation algorithm that is based on spatially adaptive color and texture features. The color features are based on the estimation of spatially adaptive dominant colors, which on one hand, reflect the fact that the human visual system cannot
simultaneously perceive a large number of colors, and on the other, the fact that colors of natural textures are spatially varying. The spatially adaptive dominant colors are obtained using a previously developed adaptive clustering algorithm for color segmentation. The
(spatial) texture features are based on a steerable filter
decomposition, which offers an efficient and flexible approximation of early processing in the human visual system. In contrast to texture analysis/synthesis techniques that use a large number of parameters to
describe texture, our segmentation algorithm relies on only a few parameters to segment the image into simple yet meaningful texture categories. Even though the estimation of the texture features requires a finite window, which limits spatial resolution, by
appropriately combining the texture and color segmentation, the proposed algorithm obtains robust, accurate, and precise
segmentations. The performance of the proposed algorithm is
demonstrated in the domain of photographic images, including low resolution, degraded, and compressed images.
Thrasyvoulos (Thrasos) Pappas received the S.B., S.M., and Ph.D. degrees in electrical engineering and computer science from MIT in 1979, 1982, and 1987, respectively. From 1987 until 1999, he was a Member of the Technical Staff at Bell Laboratories, Murray Hill, NJ.
In September 1999, he joined the Department of Electrical and Computer Engineering at Northwestern University as an associate professor. His research interests are in image and video compression, perceptual models for image processing, model-based halftoning, image and video
analysis, and multimedia signal processing. Dr. Pappas is chair of the IEEE Image and Multidimensional Signal
Processing Technical Committee, associate editor of the IEEE
Transactions on Image Processing, technical program co-chair of the
2004 Symposium on Information Processing in Sensor Networks (IPSN), and co-chair of the annual SPIE/IS&T Conference on Human Vision and Electronic Imaging. He has also served as technical program co-chair
for ICIP-2001 in Thessaloniki, Greece.