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The Application of Mathematical Morphological Optimization Algorithm in Edge Detection of Defected Wood Image

机译:数学形态学优化算法在缺陷木材图像边缘检测中的应用

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Defected woods always influence wood processing. If they are not chosen precisely, the woods will be inferior in quality. In order to obtain contours and internal information of defected woods, they are detected. Images of them are processed for the scientific usage of woods and guarantee of the increasing using rate of woods. Mathematical morphology is a new subject established based on rigorous mathematical theories. In the basis of set theory, mathematical morphology is used in image processing, analysing and comprehending. It is a powerful tool in the geometric morphological analysis and description. Based on the study of mathematical morphology, a new mathematical morphological optimization algorithm is proposed, and it is used in edge detection of defected wood images. For the purpose of suppressing noises and being adapted to different edges of defected wood images, Structuring elements of smooth diamond are chosen appropriately. Mathematical morphological optimization algorithm is constructed by weight adding combination of erosion, dilation, opening and closing operations. The results of simulation in defected wood image processing demonstrate that the method performs better in noise-suppression and edge detection than conventional edge detection operations and morphological gradient method, which also verifies its feasibility and validity. It can be extendedly used in many other fields such as furniture market, security sector and timber manufacturing industry.
机译:叛逃的伍兹总是影响木材加工。如果他们没有精确选择,那么树木就会劣等。为了获得缺陷的树林的轮廓和内部信息,它们被检测到。他们的图像是为树林的科学用法处理的,并使用树林速度增加的保证。数学形态是基于严格数学理论建立的新主题。在集合理论的基础上,数学形态用于图像处理,分析和理解。它是几何形态分析和描述中的强大工具。基于数学形态学的研究,提出了一种新的数学形态优化算法,它用于边缘检测缺陷的木材图像。出于抑制噪声并适应偏转木材图像的不同边缘,适当地选择平滑钻石的结构化元素。数学形态学优化算法由侵蚀,扩张,打开和关闭操作的重量添加组合构成。缺陷木材图像处理中的仿真结果表明,该方法在噪声抑制和边缘检测中执行比传统边缘检测操作和形态梯度方法更好,这也验证了其可行性和有效性。它可以悬而未决用于许多其他领域,如家具市场,安全部门和木材制造业。

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