基于贝叶斯相关理论的最佳阈值分割图像处理

The Optimal Threshold Segmentation Image Processing Based on Related Bayesian Theory

图像预处理是后期继续进行图像相关研究的先驱,准确有效的采用合适的预处理方法起着关键作用;在对贝叶斯公式和相关理论的深入研究后,针对贝叶斯算法处理庞大数据的高效性和处理对象的独立性强的特点,以此为基础设定整体阈值和分段阈值,并且寻找最佳阈值分割图像的方法,对人脸图像进行预处理;仿真实验得出结论表明:此法能利用短时间,清晰明了的分辨出人脸及器官,屏蔽外界影响。

Image preprocessing is the pioneer for continuing to conduct image-related studies at late time,and accurately and effectively using proper preprocessing method plays the key role.After deep study on Bayesian formula and its related theories,according to the characteristics of high-efficient mega-data processing and strong independent object processing of Bayesian algorithm,overall threshold and piecewise threshold are set and the optimal threshold segmentation method is searched,as a result,human face image is preprocessed.Simulation experiment shows that the obtained conclusion indicates that this method can take advantage of short time to clearly distinguish human face and its organs and shield outside influence.