Binary image filtering for object detection based on Haar feature density map

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).