Title :
Multi-Resolution Local Histogram Analysis for Edge Detection
Author :
Aggoun, A. ; Khallil, M.
Author_Institution :
Brunel Univ., Uxbridge
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
The objectives of this paper is to present a novel multi-resolution edge extraction algorithm, based on processing of the local histograms of small non-overlapping blocks of the output of the first derivative of a narrow 2D Gaussian filter. The proposed edge detection algorithm starts by convolving the image with a narrow 2D Gaussian smoothing filter to minimise the edge displacement, and increase the resolution and detectability. Processing of the local histogram of small non-overlapping blocks of the edge map is carried out to perform an additional noise rejection operation and automatically determine the local thresholds. It is shown that the proposed edge extraction algorithm provides the best trade off between noise rejection and accurate edge localisation and resolution.
Keywords :
Gaussian processes; edge detection; feature extraction; filtering theory; image classification; image resolution; minimisation; smoothing methods; 2D Gaussian smoothing filter; edge classification; edge detection; edge displacement minimisation; image thresholds; multiresolution edge extraction algorithm; multiresolution local histogram analysis; noise rejection; nonoverlapping blocks; Algorithm design and analysis; Computer vision; Data mining; Filters; Histograms; Image analysis; Image edge detection; Noise level; Quantization; Smoothing methods; Computer Vision; Edge Detection;
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2007.4379242