Wang Jianlun, Han Yu, Zhao Shuangshuang, Zheng Hongxu, He Can, Cui Xiaoying, Xu Yun, Chen Jianshu, Wang Shuting. A new multi-scale analytic algorithm for edge extraction of strawberry leaf images in natural light[J]. International Journal of Agricultural and Biological Engineering, 2016, 9(1): 99-108. DOI: 10.3965/j.ijabe.20160901.1310
Citation: Wang Jianlun, Han Yu, Zhao Shuangshuang, Zheng Hongxu, He Can, Cui Xiaoying, Xu Yun, Chen Jianshu, Wang Shuting. A new multi-scale analytic algorithm for edge extraction of strawberry leaf images in natural light[J]. International Journal of Agricultural and Biological Engineering, 2016, 9(1): 99-108. DOI: 10.3965/j.ijabe.20160901.1310

A new multi-scale analytic algorithm for edge extraction of strawberry leaf images in natural light

  • In this study, a new algorithm was proposed for edge extraction of greenhouse strawberry leaf in natural light based on the 4-level daubechies 5 (‘db5’) wavelet decomposition. This algorithm adopts different segmentation methods for the reconstructed images in different scales to erase the external background and the internal leaf vein interference. There were two advantages of this method. One was that it can provide the abstraction from different spaces to express a same image. The other one was that some image features are hard to be acquired in some scale spaces, while the features are easy to be obtained in other scale spaces. In this image process methods, the Otsu threshold segmentation was to obtain the binary image areas, and the Canny segmentation is to obtain the accurate gradient edges, then the morphological methods and the logical calculus methods were to avoid the fragments inside the leaf area and the adhesions outside the leaf area. Since the strawberry leaf images were different respectively, and the greenhouse optical radiation and reflection may cause local non-uniform illumination of leaf image, the pseudo canny edges of leaf image were divided into three categories in this research. The first category was the external pseudo canny edges area of the first layer reconstructed leaf image, the second category was the internal pseudo canny edges area in highlight of the third layer reconstructed leaf image, the third category was the internal pseudo canny edges area of significantly different grayscale of the third layer reconstructed leaf image. The different processing methods were constructed for the three kinds of different texture features based on the multi scale reconstructed images, then the complete and the accurate leaf edges without interference were obtained. Finally, the multi scale method was simplified and a remarkably effective segmentation algorithm was deduced for the greenhouse strawberry leaf in natural light.
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