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Conference Paper
Robust Estimation of Edge Density in Blurred Images
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- Authors
- Jae-Yeong Lee, Wonpil Yu
- Issue Date
- 2012-11
- Citation
- International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2012, pp.521-524
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Edge is an important cue for object detection in computer vision. In this paper, we present a filtering method for speeding up the object detection by using edge density as a prefiltering measure. Specifically the paper focuses on two problems of derivation of scale invariant edge density measure and robust edge extraction in blurred images. Normalization of edge density is performed based on the square root of the target area for scale invariance. Experimental result confirms validity of the suggested density measure. Second problem of edge extraction in blurred images is addressed by extracting edge pixels in scaled-down images with histogram equalization, giving more reliable edge extraction result. Experiment results on large set of pedestrian images captured under various conditions including daylight, raining, motion blur, and night are presented and analyzed quantitatively. Copyright © 2012 IEEE.
- KSP Keywords
- Blurred image, Computer Vision(CV), Density measure, Edge Extraction, Edge density, Experiment results, Experimental Result, Filtering method, Object detection, Robust Estimation, Square root