ÐA new method for unsupervised segmentation of color-texture regions in images and video is presented. This method, which we refer to as JSEG, consists of two independent steps: color quantization and spatial segmentation. In the first step, colors in the image are quantized to several representative classes that can be used to differentiate regions in the image. The image pixels are then replaced by their corresponding color class labels, thus forming a class-map of the image. The focus of this work is on spatial segmentation, where a criterion for ªgoodº segmentation using the class-map is proposed. Applying the criterion to local windows in the class-map results in the ªJ-image,º in which high and low values correspond to possible boundaries and interiors of color-texture regions. A region growing method is then used to segment the image based on the multiscale J-images. A similar approach is applied to video sequences. An additional region tracking scheme is embedded into the region growing process to achieve consistent segmentation and tracking results, even for scenes with nonrigid object motion. Experiments show the robustness of the JSEG algorithm on real images and video.
Peer group image processing identifies a "peer group" for each pixel and then replaces the pixel intensity with the average over the peer group. Two parameters provide direct control over which image features are selectively enhanced: area (number of pixels in the feature) and window diameter (window size needed to enclose the feature). A discussion is given of how these parameters determine which features in the image are smoothed or preserved. We show that the Fisher discriminant can be used to automatically adjust the peer group averaging (PGA) parameters at each point in the image. This local parameter selection allows smoothing over uniform regions while preserving features like corners and edges. This adaptive procedure extends to multilevel and color forms of PGA. Comparisons are made with a variety of standard filtering techniques and an analysis is given of computational complexity and convergence issues.
Currently there are quite a few image retrieval systems that use color and texture as features to search images. However, by using global features these methods retrieve results that often do not make much perceptual sense. It is necessary to constrain the feature extraction within homogeneous regions, so that the relevant information within these regions can be well represented. This paper describes our recent work on developing an image segmentation algorithm which is useful for processing large and diverse collections of image data. A compact color feature representation which is more appropriate for these segmented regions is also proposed. By using the color and texture features and a region-based search, we achieve a very good retrieval performance compared to the entire image based search.
Tetrandrine is known to exert antitumor effect, however, little is known about its effect on nasopharyngeal carcinoma cells. In this study, we tested tetrandrine-induced apoptosis and radiosensitivity in nasopharyngeal carcinoma cell line CNE and investigated the possible mechanisms. Using flow cytometry and DNA electrophoresis, we found that tetrandrine could induce cell apoptosis. Further, it was shown that the level of Bcl-2 mRNA decreased and Bax mRNA increased after addition of tetrandrine by using reverse transcription-polymerase chain reaction. X-ray-induced G2 arrest was abrogated by treatment with tetrandrine, as detected by flow cytometry and mitotic index. The accumulation of cyclinB1 protein and the suppression of Cdc2 tyrosine-15 and Cdc25C serine-216 phosphorylation were detected in irradiated cells treated with tetrandrine using Western blot analysis. Taken together, these results show that tetrandrine can induce apoptosis and abrogate radiation-induced G2 arrest in CNE cells.
The primary root plays essential roles in root development, nutrient absorption, and root architectural establishment. Primary root growth is generally suppressed by phosphate (P) deficiency in A. thaliana; however, the underlying molecular mechanisms are largely elusive to date. We found that AtOPR3 specifically inhibited primary root growth under P deficiency via suppressing root tip growth at the transcriptional level, revealing an important novel function of AtOPR3 in regulating primary root response to the nutrient stress. Importantly, AtOPR3 functioned to down-regulate primary root growth under P limitation mostly by its own, rather than depending on the Jasmonic acid signaling pathway. Further, AtOPR3 interacted with ethylene and gibberellin signaling pathways to regulate primary root growth upon P deficiency. In addition, the AtOPR3’s function in inhibiting primary root growth upon P limitation was also partially dependent on auxin polar transport. Together, our studies provide new insights into how AtOPR3, together with hormone signaling interactions, modulates primary root growth in coping with the environmental stress in Arabidopsis.
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