상세정보
학술대회
Robust Estimation of Edge Density in Blurred Images
- 발행일
- 201211
- 출처
- International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2012, pp.521-524
- 협약과제
- 12MC2200, 실외환경에 강인한 도로기반 저가형 자율주행 기술 개발, 유원필
- 초록
- 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 제안 키워드
- Blurred image, Computer Vision(CV), Density measure, Edge Extraction, Edge density, Experiment results, Experimental Result, Filtering method, Object detection, Robust Estimation, Square root