A new approach presented in this study to determine the optimal edge detection threshold value. This approach is base on extracting small homogenous blocks from unequal mean targets. Then, from these blocks we generate small image with known edges (edges represent the lines between the contacted blocks). So, these simulated edges can be assumed as true edges .The true simulated edges, compared with the detected edges in the small generated image is done by using different thresholding values. The comparison based on computing mean square errors between the simulated edge image and the produced edge image from edge detector methods. The mean square error computed for the total edge image (Er), for edge regions (Erl), and for non-edge regions (Er2). From these measures (Er, Erl, &Er2), we can estimate best threshold value, at low edge errors detection (i.e. best (th) at low Er, Erl,&Er2).
University of Baghdad
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