Share Email Print
cover

Proceedings Paper

Binary image filtering for object detection based on Haar feature density map
Author(s): Chengqi Li; Zhigang Ren; Bo Yang
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The most concerned problem is to detect the interesting objects in image sequence captured from the same scene. Image difference is a commonly used method in detecting the interesting object, however, massive noise exists in the binarized difference image, so how to remove the noise is a hot issue. Aiming at the removing the noise in binary difference image, we propose a novel filtering algorithm based on Haar feature density map. Firstly, calculate the Haar feature density distribution map of binary image. Secondly, the density distribution map of Haar feature is binarized to remove noise. Finally, the interesting objects can be easily detected. Experiments show that the Haar feature density map achieves a better filtering effect than the conventional filtering algorithms for binary image (such as median filtering, morphological operation and so on).

Paper Details

Date Published: 19 December 2017
PDF: 6 pages
Proc. SPIE 10613, 2017 International Conference on Robotics and Machine Vision, 1061303 (19 December 2017); doi: 10.1117/12.2300505
Show Author Affiliations
Chengqi Li, State Grid Shandong Electric Power Research Institute (China)
Zhigang Ren, State Grid Shandong Electric Power Co. (China)
Bo Yang, State Grid Shandong Electric Power Co. (China)


Published in SPIE Proceedings Vol. 10613:
2017 International Conference on Robotics and Machine Vision
Chiharu Ishii; Genci Capi; Jianhong Zhou, Editor(s)

© SPIE. Terms of Use
Back to Top