19 December 2017 Binary image filtering for object detection based on Haar feature density map
Author Affiliations +
Proceedings Volume 10613, 2017 International Conference on Robotics and Machine Vision; 1061303 (2017) https://doi.org/10.1117/12.2300505
Event: Second International Conference on Robotics and Machine Vision, 2017, Kitakyushu, Japan
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).
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chengqi Li, Zhigang Ren, Bo Yang, "Binary image filtering for object detection based on Haar feature density map", Proc. SPIE 10613, 2017 International Conference on Robotics and Machine Vision, 1061303 (19 December 2017); doi: 10.1117/12.2300505; https://doi.org/10.1117/12.2300505
PROCEEDINGS
6 PAGES


SHARE
Back to Top