Research On Image Binarization Algorithm And Its Application In Surveillance Recognition System

Image segmentation is a key technology in image processing, analysis and understanding areas. Image segmentation technology segments image into regions each with characteristics and extracts interesting targets form image. Binarization is the most commonly used method of image segmentation. By binarization, an image can be divided into two regions, each with similar gray value. By this way, the foreground and background could be presented visually. However, in most of time, we can not get correct result of foreground and background after binarization because of various unknown factors in images. Meanwhile, the complexity of binarization methods is becoming relatively higher, which limited its applications in practical engineering. Therefore, studying on fast and efficient binarization methods in image analysis, understanding, object recognition and other technology has important significance. In this paper, we focus on studying fast and efficient binarization algorithm. The principal works are as following:1) For the shortcomings of poor performance in noise immunity of one-dimensional Otsu algorithm and alarming calculation of two-dimensional Otsu algorithm. We proposed a fast two-dimensional Otsu algorithm based on histogram projection. We projected the two-dimensional histogram onto its diagonal, which formed a one-dimensional histogram with marked distribution of peaks. Based on the one-dimensional histogram, we got a point on the diagonal by one-dimensional Otsu. Then we searched the optimal thresholds on the line which is perpending to the diagonal by two-dimensional Otsu algorithm. By this way, we changed the two-dimensional threshold search into twice one-dimensional search with the same effectiveness of image binarization. Furthermore, we established three look-up table based on the two-dimensional threshold (s, t), which could accelerate the computation speed. Experiments showed that the algorithm had better noise immunity and real-time. The algorithm not only retains the segmentation of two-dimensional algorithm, but also has the segmentation speed fairly with one-dimensional algorithm.2) Gato's binarization algorithm depends on other local binarization methods in processing the degraded document images. To overcome this week point, we proposed an algorithm based on foreground estimation and GRA enhancement. In our new algorithm, we estimated background image with a modified mean filter. Furthermore, we enhanced the foreground image by GRA method. Finally, the fast two-dimensional Otsu algorithm was utilized to get binarization result. Experiment results showed that our method performed well in degraded document images.3) We designed and implemented a video surveillance recognition system according to an enterprise's work. The system intercepts images from monitored video, and recognizes the content from images after a series of processing. We made use of our new binarization method in image pre-processing and recognition of the system. The new algorithm can satisfy the system's requirements in functionality and speed. The system has been put into use presently.