Measuring the Degree of Suitability of Edge Detection Operators Prior to an Application

Abstract

Unlike image restoration, image enhancement techniques are found to be subjective in nature as the appearance of an output image depends upon human perception. Hence, it is very difficult to determine the appropriateness of image enhancement techniques including edge detection operators prior to an application. This paper makes use of regression models to determine the suitability of edge detection operators before operators to be executed. With the existing operators, a novel Hybrid technique is used in the evaluation. The Hybrid detector is designed by combining Canny and Sobel operators with the gradient of texton image. This approach estimates a model as an objective function to determine the degree of proximity or suitability of edge detection operators under regression constraints on two publicly available databases, viz. the BSDS300 and the Multi-cue. The experimental results exhibit that the Hybrid edge detector outperforms other operators for measuring the proximity for appropriateness.