Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 6
1913-1916

Cotton bolls counting algorithm in field based on density level classification

Huang Ziyun1,2
Li Yanan1,2
Wang Haihui1,2
1. School of Computer Science & Engineering, Wuhan Institute of Technology, Wuhan 430205, China
2. Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan 430073, China
DOI: 10.19734/j.issn.1001-3695.2020.06.0206

Abstract

The severe occlusion and scale variation in the cotton field reduce the accuracy of the object counting algorithm greatly. To solve above problems, this paper presented a cotton boll counting algorithm based on context multi-scale fusion. This algorithm consisted of the context module of the pyramid structure and the fusion convolutional neural network. Firstly, it adopted global context and local context modules to encode the context information in the cotton images, and then used multi-co-lumn feature conversion module to map the input image into high-dimensional feature. Finally, it combined the context information with the high-dimensional feature through the fusion convolutional neural network, for achieving high-precision cotton boll counting and generating high-quality cotton boll density map. In addition, this paper conducted experiments on the cotton boll dataset from two angles of close-range and ground-air observation. The comparative experimental results show that adopting context information can effectively improve the accuracy of cotton boll counting, and the counting errors MAE and MSE have decreased by 27.3 and 29.4, respectively.

Foundation Support

国家自然科学基金资助项目(61906139)
湖北省自然科学基金资助项目(2019CFB173)
武汉工程大学智能机器人湖北省重点实验室开放基金资助项目(HBIR201903)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0206
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: Technology of Graphic & Image
Pages: 1913-1916
Serial Number: 1001-3695(2021)06-059-1913-04

Publish History

[2021-06-05] Printed Article

Cite This Article

黄紫云, 李亚楠, 王海晖. 基于上下文多尺度融合的棉铃计数算法 [J]. 计算机应用研究, 2021, 38 (6): 1913-1916. (Huang Ziyun, Li Yanan, Wang Haihui. Cotton bolls counting algorithm in field based on density level classification [J]. Application Research of Computers, 2021, 38 (6): 1913-1916. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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