Wavelet-based edge detection
Date of Publication
2004
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Computer Science
Subject Categories
Computer Sciences
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Jocelynn Wong
Defense Panel Member
Clement Y. Ong
Roselle S. Berdin
Joel P. Ilao
Abstract/Summary
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.
Abstract Format
html
Language
English
Format
Accession Number
TU13646
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
1 v. (various foliations) : ill. (some col.) ; 28 cm.
Keywords
Computer algorithms; Wavelets (Mathematics); Image procesings--Digital techniques; Imaging systems
Recommended Citation
Dimla, C. G., Reyes, J. T., Vallejo, K. N., & Martinez, G. S. (2004). Wavelet-based edge detection. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/14229