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Research on Fruit Recognition and Classification Based on MATLAB

Published: 04 January 2021 Publication History

Abstract

Our country is a big fruit producing country, and its annual fruit output occupies the top in the world. In fruit production operations, most fruit picking is done manually. Due to the gradual transfer of agricultural labor resources to other industries in the early twentieth century, the shortage of agricultural labor has become more and more serious. Fruit picking robots can solve the shortage of labor resources and improve production efficiency. The automatic identification and segmentation technology of fruit image processing is an important part of the design of the fruit picking robot vision system. Therefore, the research on the identification and classification of fruits through computers is particularly important. In this paper, the image of apples, oranges and bananas is recognized and classified by MATLAB software.

References

[1]
Zheng Xiaodong, Wang Xiaojie, Li Yinqing.Automatic fruit recognition technology in natural environment[J].Computer Applications and Software, 2006, 23(11):96--97, 100.
[2]
Wang Shuiping, Tang Zhenmin, Fan Chunnian, et al. Research on Fruit Classification Algorithm Based on SVM[J].Journal of Wuhan University of Technology, 2010, 32(16):44--47.
[3]
Cheng Ronghua, Ma Fei, Liang Yahong.Study on automatic recognition of fruits with similar shapes[J].Shandong Agricultural Sciences, 2015, (8):116--118.
[4]
Chen Guangqiu, Wang Bingxue, Liu Mei, et al. Linear projection grayscale algorithm based on structural information similarity[J]. Journal of Jilin University (Science Edition), 2020, 58(4): 877--884.
[5]
Li Yanli. Research on mobile phone film image multi-target recognition technology based on feature union[D]. Hubei: Hubei University of Technology, 2015.
[6]
Chen Wukun.Using custom patterns to binarize color images[J].Computer Engineering, 2001, 27(5):139--140.
[7]
Zhao Hui, Li Hao, Yue Youjun, et al. Recognition and positioning of short anvil apple based on RGB-D camera[J]. Computer Engineering and Design, 2020, 41(8): 2278--2283.
[8]
Ma Ke. Research on Adaptive Edge Detection Algorithm Based on Maximum Pixel Distance[D]. Shandong: Shandong University, 2019.
[9]
Xu Changrong, Wang Congyin.Sobel edge detection based on Hadoop cluster[J].Journal of Jiangxi University of Science and Technology, 2013, (3):38--41, 74.
[10]
Niu Wenfei. Research on image segmentation method based on shape prior and graph cut[D]. Shaanxi Normal University, 2013.
[11]
Wang Guoyi, Sun Yongrong, Wu Lei, et al. Correlation tracking of circular targets with adaptive block detection scale [J]. Computer Engineering and Applications, 2020, 56(8): 177--184.
[12]
Zou Jianhua. Research on low-light image enhancement technology based on HSV color space[D]. Sichuan: Southwest University of Science and Technology, 2010.

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    ISBDAI '20: Proceedings of the 2020 2nd International Conference on Big Data and Artificial Intelligence
    April 2020
    640 pages
    ISBN:9781450376457
    DOI:10.1145/3436286
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 04 January 2021

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    Author Tags

    1. Fruit recognition
    2. MATLAB
    3. image processing

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