A further enhancement of the canny edge detection algorithm for edge detection application

ABSTRACT: Edge detection is an image processing technique for finding the boundaries of objects within images. It works by detecting discontinuities in brightness. Edge detection is used for image segmentation and data extraction in areas such as image processing, computer vision, and machine vision. The purpose of this study in general is to enhance one of the standard edge detection methods-the Canny edge algorithm. The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images. The enhanced Canny edge detector algorithm is based from the existing case study about Canny edge algorithm done by Gellegani and Gesmundo at Pamantasan ng Lungsod ng Maynila back in the year 2012. The existing Canny edge algorithm detects edges but requires manual configuration of threshold values based from the user’s and is unable to detect smooth edges and edged with bright background. On the other hand, the enhanced algorithm automatically generates threshold values, whereas it can also render significant edges accurately and produces a better edge on images with bright background which gives emphasis of the subject over the background.

Filipiniana