Improved Edge Detection Method by using Weighted Support Vector Machines

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Dr.T. Karthikeyan
N.P. Revathy


dge detection plays considerable part in recent years to various image processing applications. Detection of edge results for noise free images becomes easy and it is not applicable to practical applications .The quality of images for a practical case is degraded by noise. Detection of edges for noise image becomes more difficult task in several numbers of edge detection methods such as K means clustering, and SVM classification methods. All of these methods produce best edge detection results, but still the detection rate of methods needs to improve. In this paper presented a new weighted support vector machines (WSVM) method for edge detection. It uses different edge detection features as input to WSVM for edge detection process. This method enhances edge detection results by reducing the working out time and improvement the image quality it can be compared to existing edge detection methods. The overall performance of proposed WSVM edge detection results is high than the existing methods.

Keywords---Weighted support vector machines, Edge detection, Gradients, Image processing.


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