Wavelet-based edge detection

• Main Authors: Dimla, Celine Angela G., Reyes, Jocelyn T., Vallejo, Kristine N., Martinez, Glenn Paul S.
• Format: text
• Language: English
• Published: Animo Repository 2004
• Subjects: Computer algorithms; Wavelets (Mathematics); Image procesings > Digital techniques; Imaging systems; Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/14229
• Institution: De La Salle University

There are existing edge detection systems that are robust and effective. The most common algorithms for these systems are the Gradient and Laplacian method. Nonetheless, these algorithms have difficulties in detecting edges when the difference in contrast between the target and the background is low. Another trouble area is that they are quite susceptible to noise. The Gradient and Laplacian method are implemented in this system on low contrast images with different noise levels. In an attempt to discover a better alternative, the Wavelet algorithm was also applied to the edge detection principle. A comparative study on the speed and accuracy in the detection of edges was then performed on the three algorithms. The speed and accuracy results were quantified through the MATLAB's Stopwatch Timer function and the Pratt's Figure of Merit formula respectively. The Gradient algorithm had the fastest run-time and the Laplacian algorithm had detected the most number of accurate edges when there is no visual noise in the image. Interestingly, the Wavelet algorithm appeared to be intermediate in both its speed and its speed and its accuracy. It was also noted through visual inspection that the Bioorthogonal basis function of the Wavelet algorithm was best suited for real world images.