We aim at using color information to classify the physical nature of edges in video. To achieve physics-based edge classification, we first propose a novel approach to color edge detection by automatic noise-adaptive thresholding derived from sensor noise analysis. Then, we present a taxonomy on color edge types. As a result, a parameter-free edge classifier is obtained labeling color transitio...

We addressed the problem of automatically differentiating photographs of real scenes from photographs of paintings. We found that photographs differ from paintings in their color, edge, and texture properties. Based on these features, we trained and tested a classifier on a database of 6000 paintings and 6000 photographs. Using single features results in 70–80% correct discrimination performanc...

Given a graph G and an edge coloring C of G, an alternating cycle of G is such a cycle of G in which any adjacent edges have distinct colors. Let dc(v), named the color degree of a vertex v, be defined as the maximum number of edges incident with v, that have distinct colors. In this paper, some color degree conditions for the existence of alternating cycles of length 3 or 4 are obtained. We al...

This article presents a complete hybrid object recognition system for three-dimensional objects using the characteristic view (ChV) idea. High-quality 2-D reconstructions have to be generated from intensity or color data, respectively, to integrate the ChV representation method into a recognition system. First, we present an approach for obtaining edges and gradient information from color image...

We aim at using color information to classify the physical nature of edges in video. To achieve physics-based edge classification, we first propose a novel approach to color edge detection by automatic noise-adaptive thresholding derived from sensor noise analysis. Then, we present a taxonomy on color edge types. As a result, a parameter-free edge classifier is obtained labeling color transitio...

We propose a method of initial seed selection used for color image segmentation. In this paper Initial seed selection is a starting stage of color image segmentation. This method is based on HSV color model. Here we use two details; one is non-edge pixels and second is smoothness feature of the pixels. The non-edge pixels and smoothness at pixel’s neighbor are used as criteria to determine init...

This paper presents a new moment-preserving thresholding technique, called the binary quaternion-moment-preserving (BQMP) thresholding, for color image data. Based on representing color data by the quaternions, the statistical parameters of color data can be expressed through the definition of quaternion moments. Analytical formulas of the BQMP thresholding can thus be determined by using the a...

In order to research the problem of the gray edge and leaving out some edges during detecting the color edges, the color contrast enhancement algorithm is designed that it dependences on decomposing the interrelated color component of the color images based on RGB color model. And the edge detection improved method is proposed based on the above algorithm. Namely, the components edges are compu...

In this paper, we present a logo and trademark retrieval system for general, unconstrained, color image databases that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in images, in ...

Most of the digital cameras used now has single sensor with an array of color filters to capture the digital images. Color Filter Array (CFA) uses alternating color filters to sample only one color of a pixel location to reduce the price. In the entire image, only one third of sampled pixels have genuine values from the sensors. Remaining pixels are interpolated from these genuine values. In th...