Modelling by fuzzy approach uncertainties in image analysis

E. Pap, Djordje Obradović, Z. Konjovic
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引用次数: 1

Abstract

Investigating some objects in all areas, they are mapped to the digital raster image using different kinds of sensors, the obtained image is only an approximation to the real-world object. Due to imperfections in either the image data or the edge detector, there may be missing points or pixels on lines as well as spatial deviations between ideal line and the set of imprecise points obtained from the edge detector. The overall effect is an image that has some distortion in its geometry. In this paper it is presented a mathematical model based on fuzzy sets. In this way there covered these uncertainties, and it is obtained correct interpretation and important decisions in different important areas as image analysis (imprecise feature extraction), GIS (imprecise spatial object modelling), robotics (environment models), and in medicine (DICOM medical images).
模糊方法在图像分析中的不确定性建模
在研究各个区域的某些物体时,使用不同类型的传感器将其映射为数字光栅图像,所获得的图像仅是真实物体的近似值。由于图像数据或边缘检测器的缺陷,可能会出现直线上缺失点或像素,以及理想直线与边缘检测器获得的不精确点集之间的空间偏差。整体效果是图像的几何形状有一些扭曲。本文提出了一种基于模糊集的数学模型。这样就覆盖了这些不确定性,并在不同的重要领域获得了正确的解释和重要的决策,如图像分析(不精确的特征提取)、GIS(不精确的空间对象建模)、机器人(环境模型)和医学(DICOM医学图像)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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