document: Robust and automatic thresholding of gray level images has been commonly used in the field of pattern recognition and computer vision for objects detecting, tracking and recognizing. The Otsu scheme, a widely used image thresholding technique, provides approving results for segmenting a gray level image with only one modal distribution in gray level histogram. However, it provides poor results if the histogram of a gray level is non-bimodal. For enhancing the performance of the Otsu algorithm further, in this work, an improved median-based Otsu image thresholding algorithm is presented. Finally extensive tests are performed and the experiments show that our method obtain more satisfactory results than the original Otsu thresholding algorithm.
extractive_keyphrases: computer vision detecting enhancing the performance extensive tests gray level image gray level images histogram image thresholding technique modal distribution otsu algorithm otsu scheme otsu thresholding algorithm pattern recognition recognizing robust and automatic thresholding segmenting thresholding tracking
abstractive_keyphrases: gray level histogram. median-based otsu image thresholding algorithm objects detecting, tracking and recognizing