查询结果： 侯兆静，冯全，张涛．基于高斯混合模型的叶片检测分割算法[J]．计算机应用与软件，2018，35(1)：253 - 260．
LEAF DETECTION SEGMENTATION ALGORITHM BASED ON GAUSSIAN MIXTURE MODEL
甘肃农业大学机电工程学院 甘肃 兰州 730070
School of Mechanical and Electrical Engineering,Gansu Agricultural University,Lanzhou 730070,Gansu,China
Gaussian mixture model
侯兆静，学士，主研领域：电气工程及其自动化。冯全，教授。张涛，学士。 [HJ2.5mm] 。
In order to tackle the problems to segmentation of leaf images arising from variation of illumination and appearance of a leaf as well as cluttered background, a combined segmentation method was presented. The method used a sliding window scanning method to detect the blades in the image at a plurality of scales. The initial region of the center of the leaf was used as the initial foreground, and the area outside the leaf window was used as the initial background, and the initial probability model was established for the foreground and background with the Gaussian mixture model (GMM). The segmentation was carried out by the iterative method in which the standard Graph Cut, combing with GMMs which was gotten in previous round, was used to segment the leaves in each round, and the results to update GMMs of the foreground and background. For leaves detection, HOG feature was exploited which could describe the appearance and shape of a leaf. To solve challenges of variations of appearance and viewpoint to accurate detection, we adopted a strategy of multiple-subcategory classifiers for the leaves. We took the grape leaf as an example to evaluate the performance of the proposed segmentation method. The experimental results showed that our method worked very well on condition of aforementioned challenges, exhibiting robustness and accuracy. Furthermore, the proposed method can fulfill auto-segmentation completely.