An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized r...An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized region is approximated with linear type of segments. Then a rectangle belt is constructed for each segment. Finally, the gray value distribution in the region is fitted by normal forms polynomials. The model matching and motion analysis are also based on the architecture of sensitized region. For the smooth region we use the run length scanning and linear approximating. By means of normal forms polynomial fitting and motion prediction by matching, the images are compressed. It is shown through the simulations that the subjective quality of reconstructed picture is excellent at 0.0075 bit per pel.展开更多
The perfect image retrieval and retrieval time are the two major challenges inCBIR systems. To improve the retrieval accuracy, the whole database is searched basedon many image characteristics such as color, shape, te...The perfect image retrieval and retrieval time are the two major challenges inCBIR systems. To improve the retrieval accuracy, the whole database is searched basedon many image characteristics such as color, shape, texture and edge information whichleads to more time consumption. This paper presents a new fuzzy based CBIR method,which utilizes colour, shape and texture attributes of the image. Fuzzy rule based systemis developed by combining color, shape, and texture feature for enhanced image recovery.In this approach, DWT is used to pull out the texture characteristics and the region basedmoment invariant is utilized to pull out the shape features of an image. Color similarityand texture attributes are extorted using customized Color Difference Histogram (CDH).The performance evaluation based on precision and BEP measures reveals the superiorityof the proposed method over renowned obtainable approaches.展开更多
文摘An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized region is approximated with linear type of segments. Then a rectangle belt is constructed for each segment. Finally, the gray value distribution in the region is fitted by normal forms polynomials. The model matching and motion analysis are also based on the architecture of sensitized region. For the smooth region we use the run length scanning and linear approximating. By means of normal forms polynomial fitting and motion prediction by matching, the images are compressed. It is shown through the simulations that the subjective quality of reconstructed picture is excellent at 0.0075 bit per pel.
文摘The perfect image retrieval and retrieval time are the two major challenges inCBIR systems. To improve the retrieval accuracy, the whole database is searched basedon many image characteristics such as color, shape, texture and edge information whichleads to more time consumption. This paper presents a new fuzzy based CBIR method,which utilizes colour, shape and texture attributes of the image. Fuzzy rule based systemis developed by combining color, shape, and texture feature for enhanced image recovery.In this approach, DWT is used to pull out the texture characteristics and the region basedmoment invariant is utilized to pull out the shape features of an image. Color similarityand texture attributes are extorted using customized Color Difference Histogram (CDH).The performance evaluation based on precision and BEP measures reveals the superiorityof the proposed method over renowned obtainable approaches.
