In this paper, we propose an improved approach for image segmentation based on color and local homogeneity features. A given image is transformed into a quantized image by a self-constructing fuzzy clustering. Then, a color-based region image and an initial seeded region image are obtained from the quantized image by color-based and homogeneity-based region growing methods, respectively. After that, we combine these two images to generate a refined seeded region image and obtain an initial segmented image by a region-based region growing. Finally, merging based on color similarities and sizes of regions is performed for avoiding the problem of over-segmentation. Compared with the other method, experimental results show that the segmented regions obtained by our approach are more reasonable and precise.
Owning to the rapid development of Internet, users have more chances to use multimedia data and digi tal contents. As a result, illegal reproduction of digi tal information started to pose a real problem. Digital watermarking has been regarded as an effective solu tion to protect various kinds of digital contents against illegal use. In this paper, a watermarking technique which applies the discrete cosine transformation and z-score transformation is presented. In order to im prove the performance of watermarking technique, a genetic algorithm is used to search proper parameters which are used to control the watermark strength. Ex perimental results demonstrates that the proposed tech nique is able to withstand a variety of attacks.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.