Abstract
Homomorphic filtering and improved k-means algorithm were used to solve the problem of apple surface reflection and apple shadow caused by uneven light during apple grading. Before homomorphic filtering, the apple image was converted from RGB space to HSV space. Then the V component of HSV space was enhanced by homomorphic filtering to minimize the impact of uneven light. For the traditional K-means clustering algorithm, distance measurement method, determination of clustering number and initial center point were newly added, which can better remove the influence of apple shadow on image segmentation. The Qin Guan apples in Fu Xian county of northern Shaanxi were classified from five aspects, such as size, shape, quality, color and defect. Compared with the artificial and mechanical classification, the classification success rate reached 97%. Using homomorphic filtering algorithm and improved k-means algorithm to process apple images can greatly improve the accuracy of apple classification.
Publication Date
12-28-2019
First Page
47
Last Page
51,112
DOI
10.13652/j.issn.1003-5788.2019.12.009
Recommended Citation
Yangyang, WANG; Xun, HUANG; Hao, CHEN; Lun, HUANG; and Yangbo, LEI
(2019)
"Research on apple classification algorithm based on homomorphic filtering and improved K-means algorithm,"
Food and Machinery: Vol. 35:
Iss.
12, Article 9.
DOI: 10.13652/j.issn.1003-5788.2019.12.009
Available at:
https://www.ifoodmm.cn/journal/vol35/iss12/9
References
[1] CUCCHIARA R, GRANA C, PICCARDI M, et al. Improving shadow suppression in moving object detection with HSV color information[C]// Proceedings of 2001 IEEE Intelligent Transportation Systems. [S.l.]: IEEE, 2001: 334-339.
[2] 刘艳丽, 石俊, 张严辞. 一种单幅室外图像的阴影去除算法[J]. 软件学报, 2012, 23(2): 168-175.
[3] SUN Bang-yu, LI Shu-tao. Moving cast shadow detection of vehicle using combined color models[C]// 2010 Chinese Conference on Pattern Recognition (CCPR). [S.l.]: IEEE, 2010: 1-5.
[4] QU Liang-qiong, TIAN Jian-dong, HAN Zhi, et al. Pixel-wise orthogonal decomposition for color illumination invariant and shadow- free image[J]. Optics Express, 2015, 23(3): 2 220-2 239.
[5] 刘义红. 一种改进的K-means聚类自然图像分割算法设计与实现[J]. 淮南师范学院学报, 2018, 20(2): 125-130.
[6] 焦竹青. HSV变换和同态滤波的彩色图像光照补偿[J]. 计算机工程与应用, 2006, 46(30): 142-144.
[7] 张亚飞, 谢明鸿. 基于HSI和局部同态滤波的彩色图像增强算法[J]. 计算机应用与软件, 2013(12): 35-56.
[8] 许子杰, 任光亮. 基于马氏距离的相位噪声抑制算法[J]. 华中科技大学学报: 自然科学版, 2017(4): 47-62.
[9] MARTINS A, DUARTE A, DANTAS J, et al. A new clustering separation measure based on negentropy[J]. Journal of Control, Automation and Electrical Systems, 2015, 26(1): 28-45.
[10] 李金涛, 艾萍, 岳兆新, 等. 基于K-means聚类算法的改进[J]. 国外电子测量技术, 2017(6): 30-47.