Title :
Rough edge detection of low contrast images using consequential local variance maxima
Author :
Lee, Gyu-Dong ; Kim, Kwang-Sub ; Jeong, Dong-Seok
Author_Institution :
Dept. of Electron. Eng., Inha Univ., Inchon, South Korea
Abstract :
This paper suggests a new edge detection method using local variance maxima which can be applied for finding an auto license plate (ALP) with over 98% success rate in a practical situation. We determine whether a certain point belongs to an edge or not by its length of consequential local variance maxima instead of its magnitude. This is a distinguished difference from the other edge detection methods. The proposed method works effectively even for images of low contrast. This method finds edges by a single pass, with line by line scanning that means no preprocessing and small time consumption
Keywords :
computer vision; edge detection; Korean auto license plate; edge detection methods; line scanning; local variance maxima; low contrast images; machine vision; rough edge detection; smoothing filters; success rate; Cameras; Clouds; Image edge detection; Image segmentation; Iris; Layout; Licenses; Shape; Sun; Vehicles;
Conference_Titel :
TENCON 99. Proceedings of the IEEE Region 10 Conference
Conference_Location :
Cheju Island
Print_ISBN :
0-7803-5739-6
DOI :
10.1109/TENCON.1999.818519