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Date of Award
Spring 1992
Rights
Access perpetually restricted to EWU users with an active EWU NetID
Document Type
Thesis: EWU Only
Degree Name
Master of Science (MS) in Computer Science
Department
Computer Science
Abstract
Computer image processing often involves three processing stages : 1. detecting and extracting edges from the input image, 2. connecting the detected edges to form objects, 3. using information about the objects to construct and understand a scene. Edge detecting is an important processing stage. The intent of this research is to explore the possibility of using neural computing algorithms for edge detection in binary images. This paper presents the following : 1. the experimental results of using the basic backpropagation algorithm for edge detecting in binary images. 2. the development of a new neural computing algorithm and the results of applying it on edge detecting in binary images. 3. evaluation of the new algorithm. 4. comparison of the new algorithm with a conventional edge detecting method. In order to bring this research under a realistic light, the new algorithm was also experimented on the edge detection of the left ventricle area in a MRI scan of a human heart.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Tian, Jun, "A study of using backpropagation and a new neural net algorithm for edge detecting in binary images" (1992). EWU Masters Thesis Collection. 874.
https://dc.ewu.edu/theses/874
