Title :
An Image Edge Detection Algorithm Based on One-Dimensional Discrete Wavelet Signal-Noise Separation
Author :
Xingyi Li ; Xiaoli Zhao
Author_Institution :
Sch. of Comput. Sci. & Telecommun. Eng., Jiangsu Univ., Zhenjiang, China
Abstract :
By using wavelet transform modulus maxima method to detection image edge, edge details are easily smoothed out in the large scale analysis and related parameters great influenced by the noise is not easy to extract in traditional small scale analysis. To solve this problem, this paper proposes a method based on one-dimensional discrete wavelet image edge detection. This algorithm decompose image into one-dimensional signal, making signal-noise separation with one-dimensional discrete wavelet, and detect the edge of de-noised signal´s high frequency components. The article has experimented the multiple vehicle detection in real scene for many times, and the result shows that this algorithm solved the problem that exist in wavelet transform modulus maxima method to test image edges in small scale analysis, restraining noise better, and had higher precision in edge localization.
Keywords :
discrete wavelet transforms; edge detection; object detection; source separation; edge localization; image edge detection algorithm; large scale analysis; multiple vehicle detection; noise separation; one-dimensional discrete wavelet signal-noise separation; small scale analysis; wavelet transform modulus maxima method; Discrete wavelet transforms; Filtering algorithms; Image edge detection; Noise; Vehicles; Edge detection; Signal-noise separation; Vehicle identification; Wavelet transformation;
Conference_Titel :
Intelligent Systems (GCIS), 2012 Third Global Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4673-3072-5
DOI :
10.1109/GCIS.2012.10