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Medical Image Enhancement Using Morphological Transformation
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作者 Raihan Firoz Md. Shahjahan Ali +3 位作者 M. Nasir Uddin Khan Md. Khalid Hossain Md. Khairul Islam Md. Shahinuzzaman 《Journal of Data Analysis and Information Processing》 2016年第1期1-12,共12页
Medical imaging includes different modalities and processes to visualize the interior of human body for diagnostic and treatment purpose. However, one of the most common degradations in medical images is their poor co... Medical imaging includes different modalities and processes to visualize the interior of human body for diagnostic and treatment purpose. However, one of the most common degradations in medical images is their poor contrast quality and noise. The existence of several objects and the close proximity of adjacent pixels values make the diagnostic process a daunting task. The idea of image enhancement techniques is to improve the quality of an image. In this study, morphological transform operation is carried out on medical images to enhance the contrast and quality. A disk shaped mask is used in Top-Hat and Bottom-Hat transform and this mask plays a vital role in the operation. Different types and sizes of medical images need different masks so that they can be successfully enhanced. The method shown in this study takes a mask of an arbitrary size and keeps changing its size until an optimum enhanced image is obtained from the transformation operation. The enhancement is achieved via an iterative exfoliation process. The results indicate that this method improves the contrast of medical images and can help with better diagnosis. 展开更多
关键词 Medical Image Image Enhancement Morphological transform Top-Hat transform bottom-hat transform MATLAB
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非结构环境下基于HoG与SVM的汽车油箱盖视觉检测方法 被引量:2
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作者 梁铭裕 黄平 刘修泉 《机床与液压》 北大核心 2022年第8期20-25,共6页
为解决在自然场景中进行汽车油箱盖定位的问题,提出一种非结构环境下基于HoG与SVM的汽车油箱盖视觉检测方法。对汽车图像进行预处理并采用多尺度底帽变换提取图像暗细节特征;利用改进的最大熵阈值分割法分割图像;采用连通区域标记法对... 为解决在自然场景中进行汽车油箱盖定位的问题,提出一种非结构环境下基于HoG与SVM的汽车油箱盖视觉检测方法。对汽车图像进行预处理并采用多尺度底帽变换提取图像暗细节特征;利用改进的最大熵阈值分割法分割图像;采用连通区域标记法对二值图进行统计,并在原图中确定目标候选区域;采用HoG特征和支持向量机对候选区域进行分类判决,从而定位汽车油箱盖。结果表明:该方法可以准确地检测出油箱盖位置,即使图像存在光照不均匀、汽车覆盖件表面灰尘、细节模糊等情况,也有较好的定位效果。 展开更多
关键词 视觉检测 多尺度底帽变换 最大熵阈值分割 支持向量机(SVM) HOG特征
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