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基于形态学和小波变换的烟叶病斑分割

  

  1. 1. 西华大学机械工程学院，四川 成都 610039；
    2. 电子科技大学示范性微电子学院，四川 成都 611731
  • 出版日期:2018-10-31 发布日期:2018-11-16
  • 基金资助:
    四川省成都市科技局项目(2015-NY02-00336-NC)；江西省图像处理与模式识别重点实验室开放基金项目(TX201604005)；江西省科技支撑 计划重点项目(20161BBF60091)；西华大学研究生创新基金项目(ycjj2017032)

Research on the Method of Tobacco Leaf Disease Spot Segmentation Based on Morphology and Wavelet Transform

  1. 1. School of Mechanical Engineering, Xihua University, Chengdu Sichuan 610039, China; 
    2. Pilot School of Microelectronics, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China
  • Online:2018-10-31 Published:2018-11-16

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摘要： 烟叶病虫害分割是提高烟叶质量的重要保证。针对传统分割方法的分割精度和效 率不够理想的问题，提出了一种结合形态学和小波变换的 Otsu 算法用于烟叶病斑的分割。首先 对背景区域进行数学形态学处理，获得烟叶的叶面图像；然后选择小波系数分解叶面图像，再 将分解后的图像进行低频重构，去除噪声的影响；最后应用 Otsu 算法对叶面图像进行二次分割 得到病斑。由于形态学的开、闭运算分别能提取图像中的明暗细节特征，所以该分割方法能有 效减少背景对病斑区域的干扰，从而提高分割精度和效率；通过小波多分辨率分解，可以克服 冗余信息和噪声的影响，进一步提高了分割的精度。采用不同种类的烟叶病斑图像进行实验， 结果表明，该方法能够有效地分割出烟叶病斑，并且也适合于分割其他作物的病害。

关键词: 形态学, 小波变换, Otsu 算法, 烟叶病斑, 图像分割

Abstract: Tobacco leaf disease and insect spot segmentation is an important guarantee to improve the quality of tobacco leaves. The traditional segmentation method falls short of the desired accuracy and efficiency. Aimed at this problem, a method of Otsu combining morphological and wavelet transform to divide tobacco leaf spot is presented. Firstly, the background area is processed by mathematical morphology in Otsu to get the image of tobacco leaf. Then the leaf image is decomposed by wavelet coefficients, after which the decomposed image is to be reconstructed with low-frequency so as to undo noise effects. Finally, the disease spots will emerge after the quadratic segmentation of the image in Otsu. Thanks to the morphological opening-and-closing operation that can extract the brightness details of the image, thus this method can effectively reduce the impacts from background onto the disease-spot area, which is to improve the accuracy and efficiency of segmentation. Meanwhile, segmentation precision can be further raised by multi-scale wavelet resolving to overcome the effects from redundancy and noise. The images of different sorts of tobacco leaf spots experimented, the results show that Otsu can effectively segment the tobacco disease spot, and operate on the lesions in other plants.

Key words: morphology, wavelet transform, Otsu method, tobacco disease spot, image segmentation