| 改进的Otsu法在电梯门ROI提取中的应用 |
投稿时间：2018-03-30 修订日期：2018-04-08  点此下载全文 |
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| 中文摘要:针对传统电梯门安全保护方式的不足，开展了以阈值分割算法为核心的电梯门图像处理的研究。针对传统Otsu算法在目标区域具有低熵特点且背景区域较大的情况下无法得到理想分割阈值的问题，提出了一种基于波谷混合加权因子的全阈值分割算法，使得分割阈值处于电梯门灰度直方图谷底附近且更接近电梯门ROI（Region Of Interest，ROI）。同时结合电梯门图像特征缩小了算法的搜索范围。实验仿真表明，改进的算法相比于传统Otsu法和其他改进算法在电梯门图像的分割结果中，目标区域更接近于电梯门ROI，运算效率在同等仿真环境下更高。 |
| 中文关键词:图像分割1 图像熵2 邻域频率信息3 波谷加权4 改进Otsu5 二值化6 图像处理7 电梯安全8 |
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| Application of an improved Otsu method in ROI extraction of elevator door images |
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| Abstract:The study on elevator door image processing based on threshold segmentation algorithm was carried out to address the inadequacy of traditional elevator door protection methods. The traditional Otsu methods cannot obtained the satisfactory segmentation threshold values in some cases, such as the image entropy of targeted region is low and the background is relatively large. In order to solve this problems, a full-threshold segmentation algorithm based on mixing weighting valley-emphasis methods is proposed. And it ensured the segmentation threshold values near the valley of grey level histogram with low image entropy in elevator door image’s targeted region. In order to increase the segmentation efficiency, the image features were considered and the search scope of this method was derived and narrowed. Simulation results indicate that, as compared with the segmentation results of traditional Otsu method and other improved methods, the targeted region segmented by this methods was much closer to the Region Of Interest (ROI) in elevator door images. Additionally, calculation efficiency was improved under the same simulation environment. |
| keywords:Image segmentation1 image entropy2 neighborhood frequency3 information valley- emphasis method4 valley- emphasis methods5 Binarization 6 Image Processing 7 Elevator Safety |
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