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Image enhancement using morphological contrast enhancement for video based image analysis

机译:基于视频的图像分析的形态对比增强图像增强

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Image enhancement using morphological operations for video based image is proposed in this paper. Morphological operations used are top-hat and bottom-hat transformation. Top-hat transformation is used to extract the bright areas, and bottom-hat transformation is used to extract dark areas. Contrast enhancement processed by adding bright areas to original image and subtracting by dark areas. Morphological contrast enhancement applied to the preprocessing to generate output image for segmentation process. In this study, it conducted a comparison of the preprocessing based on the quality of clusters produced through the segmentation process. Silhouette coefficient is used to measure the validity of cluster generated in the segmentation process. The silhouette width value of the segmentation results are closed to 1 that expressed as a good cluster. Silhouette value of morphological contrast enhancement is higher than histogram equalization method. Silhouette width value of each preprocessing was 0.7729 and 0.5794, for morphological and CHE, respectively.
机译:本文提出了使用用于视频图像的形态操作的图像增强。使用的形态学操作是顶帽和底帽的转化。顶部帽子转换用于提取明亮的区域,底部帽子转换用于提取黑暗区域。通过将明亮区域添加到原始图像并减少黑暗区域来处理对比度增强。适用于预处理的形态对比度增强,以产生分割过程的输出图像。在该研究中,它对基于通过分割过程产生的簇的质量进行了预处理的比较。剪影系数用于测量分段过程中生成的群集的有效性。分段结果的轮廓宽度值关闭为1表示为良好群集的1。形态对比增强的轮廓值高于直方图均衡方法。每个预处理的轮廓宽度值分别为0.7729和0.5794,用于形态学和Che。

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