In this paper we propose a method to detect human faces in color images , that uses a combination of color spaces and edge detection for segmentation. Algorithm ingeniously combines different color space models, specifically, HSI and YCbCr along with Canny and Prewitt edge detection techniques.Experimental results indicate improved false acceptance rates. The overall performance of the face det...

In this paper, we propose a parallel genetic algorithm for cell image segmentation under severe noise. Our contribution aims at overcoming the drawback of the slow convenence of the traditional genetic algorithm, which was used in our previous work. A priori knowledge about cell shape is incorporated in our method. That is, an elliptical cell contour model is introduced to describe the boundary...

We introduce an edge detection and recovery framework based on open active contour models (snakelets). This is motivated by the noisy or broken edges output by standard edge detection algorithms, like Canny. The idea is to utilize the local continuity and smoothness cues provided by strong edges and grow them to recover the missing edges. This way, the strong edges are used to recover weak or m...

This paper discusses the poor performance of the Canny edge detector at junctions formed by three edges, where connectivity is usually destroyed in an arbitrary way. This problem is shown to be due to the non-maximal suppression algorithm, used to identify points of inflection in the grey-level surface. A method to overcome the problem, based on local evidence in the gradient vector, is reporte...

Relational Over the last two decades, the advances in computer vision and pattern recognition power have opened the door to new opportunity of automatic facial expression recognition system[1]. This paper use Canny edge detection method for facial expression recognition. Image color space transformation in the first place and then to identify and locate human face .Next pick up the edge of eyes...

One of the difficult problems recognized in image processing and pattern analysis, in particular in medical imaging applications is boundary detection. The detection of skin lesion boundaries accurately allows, skin cancer detection .There is no unified approach to this problem, which has been found to be application dependent. Early diagnosis of melanoma is a challenge, especially for general ...

Edges represent significant boundary information between objects or classes. Various methods, which are based on differential operation, such as Sobel, Prewitt, Roberts, Canny, and etc. have been proposed and widely used. The methods are based on a linear convolution of mask with pre-assigned coefficients. In this paper, we propose an edge detection method based on Dempster-Shafer's evidence th...

Vessel segmentation is a key step for various medical applications, such as diagnosis assistance, quantification of vascular pathology, and treatment planning. This paper describes an automatic vessel segmentation framework which can achieve highly accurate segmentation even in regions of low contrast and signal-to-noise-ratios (SNRs) and at vessel boundaries with disturbance induced by adjacen...

This paper presents an edge detection method based on global and local parameters of the image, which produces satisfactory results on the edge detection of complex images and has a simple structure for execution. The local and global parameters of the image are arithmetic means and standard deviations, the former acquired from a three sized window representing five pixels, the latter acquired ...

This paper addresses a problem of restoring handwritten archival documents by recovering their contents from the interfering handwriting on the reverse side caused by the seeping of ink. We present a novel method that works by first matching both sides of a document such that the interfering strokes are mapped with the corresponding strokes originating from the reverse side. This facilitates th...