灰度位图背景杂质剔除算法的优化

本文主要针对目前痕迹识别中采集的具有背景杂质的灰度位图（.bmp）,通过离散区域与连通区域的数目统计,然后不同灰度级区域进行标识,设计出了两种更为优化的灰度位图（.bmp）背景杂质剔出的算法,并提出了两种算法整合使用的设计思路,算法实现了更高效高准确性的图像结果,在痕迹识别系统、人脸识别系统等应用领域中大大提高了整体程序的运算速度、更高效更准确的剔除图像背景杂质,得到最优化的图像结果.

Optimization of Removed Algorithm in the Grayscale Bitmap Background Impurities

This paper is about the design of two more optimized grayscale bitmap （BMP） background impurities-eliminating algorithm, and proposes two design ideas of Combination of two algorithms. The essay aims at the gray background bitmap collected from the current identification with traces of impurities, on the basis of the statistic of regional and connected areas. As a result, The overall program operation speed will be greatly improved in the system of traces-identification and face-recognition, image background impurities will be eliminated more effectively and accurately, so that optimal image results will come up.