TY  - BOOK
AU  - Norman Robert R. Gellegani and Benedict Clarion U. Gesmundo.
AU  - 
ED  - 
ED  - 
ED  - 
ED  - 
SN  - 2
PY  - 2013///.46
CY  - 
PB  - 
KW  - 
KW  - 2
KW  - 0
KW  - 6
KW  - 20
N1  - Undergraduate Thesis: (BSCS major in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2013; 5
N2  - ABSTRACT:  	The purpose of this study is to show the capability of the Canny algorithm in rendering of edges from a source image. The enhanced Canny edge detector algorithm is based from the existing case study about Canny edge detector algorithm done at Lappeenta University back in the year 2009.  	The existing Canny edge detector algorithm detects prominent edges but is produced together with noise and other unwanted edges due to constant values being passed around the algorithm. On the other hand, the enhanced algorithm render edges with high precision and produces a much cleaner output which gives emphasis of the subject over the background.  	This study focuses on rendering prominent edges in an image to detect its main features. The program accepts files with .jpeg, .jpe, .png, .bmp, and .ico types. Results show that the enhanced Canny edge detector algorithm is better compared to the existing Canny edge detector in terms of output quality
ER  -