The application of mathematical morphological optimization algorithm in edge detection of defected wood image

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.