Abstract
When the betel nut bittern is in the process of betel nut bittern, the betel nut needs to be loaded first. In this process, there will be some places in the wobble plate that are not equipped with betel nut. In turn, it will cause the machine to perform bittern on empty positions, causing waste of bittern and reducing the efficiency of bittern. In view of the situation that the machine is leaking or emptying the betel nut on the betel nut swing plate, it is necessary to identify the betel nut on the bittern plate before the bite point. Due to the large difference in color between the betel nut and the betel nut wobble plate, in order to be able to completely segment the betel nut from the wobble plate without over-segmentation or under-segmentation, an image segmentation method based on H component is proposed to identify betel nut. In this method, the acquired RGB color image is first gamma-enhanced and then transferred to the HSV color space, the HSV color space is separated, and the H channel image is obtained. The H component image is segmented by the Otsu image segmentation method, combining image morphology and regional growth The method removes the holes and small connected areas in the binary image, and finally marks the identified betel nuts by drawing a rectangular frame. Experimental results show that using this method can completely separate betel nuts from the background, without over-segmentation or under-segmentation, Thus accurately identifying betel nuts.
Publication Date
2-18-2023
First Page
95
Last Page
98
DOI
10.13652/j.issn.1003-5788.2020.12.020
Recommended Citation
HUNAG, Liang-pei; SHU, Yong; WANG, Xian; and LIU, Yang
(2023)
"Research on recognition method for automatic orientating betel nut,"
Food and Machinery: Vol. 36:
Iss.
12, Article 20.
DOI: 10.13652/j.issn.1003-5788.2020.12.020
Available at:
https://www.ifoodmm.cn/journal/vol36/iss12/20
References
[1] 杜鹏.槟榔点卤关键技术研究与结构设计[D].湘潭:湘潭大学,2017:3-6.
[2] 姜良兴.槟榔点卤连续生产线的设计与研究[D].湘潭:湘潭大学,2018:2-6.
[3] 许月明,蔡健荣,龚莹辉.基于计算机视觉的槟榔分级研究[J].食品与机械,2016,32(8):91-94,102.
[4] 朱泽敏,张东波,张莹,等.基于语义分割的槟榔内核轮廓检测[J].计算技术与自动化,2019,38(4):105-112.
[5] 车金庆,王帆,吕继东,等.重叠苹果果实的分离识别方法[J].江苏农业学报,2019,35(2):469-475.
[6] 张永梅,李菊霞.成熟花椒果实的自动识别技术研究[J].农业技术与装备,2019(1):4-6.
[7] 刘芳,刘玉坤,林森,等.基于改进型YOLO的复杂环境下番茄果实快速识别方法[J].农业机械学报,2020,51(6):229-237.
[8] MA Xu,DENG Xiang-wu,QI Long,et al.Fully convolutional network for rice seedling and weed image segmentation at the seedling stage in paddy fields[J].PloS One,2019,14(4):e0215676.
[9] ANINDITA S,HAMDANI H,HELIZA R H,et al.Automatic image segmentation of oil palm fruits by applying the contour-based approach[J].Scientia Horticulturae,2020,261:108939.
[10] 杨先凤,李小兰,贵红军.改进的自适应伽马变换图像增强算法仿真[J].计算机仿真,2020,37(5):241-245.
[11] 马玲,张晓辉.HSV颜色空间的饱和度与明度关系模型[J].计算机辅助设计与图形学学报,2014,26(8):1 272-1 278.
[12] OTSU N.A threshold selection method from grey-level histograms[J].IEEE Trans System Man Cybernet,1979,9(1):62-66.
[13] 王祥,罗素云.基于Otsu阈值与形态学处理的车道线检测[J].农业装备与车辆工程,2019,57(10):69-72.