(untitled) (Journal of Fiber Bioengineering and Informatics, 2013)
In computer vision applications, human detection occupies an important position. HOG (Histograms of Oriented Gradient) is a classical algorithm which was used in the area of object detection. But the complex background would greatly affect the test accuracy when taking HOG as a human characteristic for human detection. In order to improve the accuracy of human detection, this paper applied a new algorithm which was based on foreground segmentation. We could get each closed region by Oriented Watershed Transform and Ultrametric Contour Map, then the foreground and the background could be distinguished. Finally we removed the background and calculated the foreground characteristic. The experimental results show that this approach was effective in improving detection accuracy.