novel object detection technique for videos with homogeneous background

Abstract

Object detection and tracking in video frames play a major role in all the computer vision systems. Several computer vision systems use background subtraction method for detecting the objects. However, Background subtraction method often results in lack of accuracy during frame comparison. Also, it leads to increase in memory requirements and computational complexity while setting threshold. The new Local Mean Diamond Pattern (LMDP) is introduced here to overcome the existing issues by extracting the objects directly from the frames. The extracted objects are tracked using mean shift tracking algorithm. The experimental result shows that the LMDP outperforms the existing methods viz., Local Binary Pattern (LBP), Local Extrema Pattern (LEP) and Local Rhombus Pattern (LRP) in terms of accuracy.