Summary: Image segmentation and recognition through edge detection techniques are addressed intensively as the number of applications that contribute to image area arises. Edge detection techniques are emerged as subtle methods for image recognition paradigm. The aim of this paper is to evaluate and compare the performance of four well-known edge detector methods in finding and detecting the physical objects inside the image. Sobel, Kirsch, Vertical and Horizontal techniques detectors are applied on gray-scale 2D synthesis and real images in Jordan. The evaluation of the methods is contributed through both subjective and objective evolutions. The implementation of these techniques is accomplished using C\# programming languages. The comparative study between the four techniques indicates that the Sobel detector performance in discovering the points of strength in images was better than the Kirsch, Vertical and Horizontal techniques. Hence, we recommend Sobel as a useful edge detector technique in detecting the images boundary.