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A Method of Penicillin Bottle Defect Inspection Based on BP Neural Network

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Book cover Image and Graphics Technologies and Applications (IGTA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1043))

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Abstract

Penicillin bottles are widely used in freeze-drying product packaging. Under the strict GMP standard, every bottle filled with freeze-drying should be inspected before being sent to the market. Traditionally, the inspection is accomplished by grueling and time-consuming human work. To address this problem, a method based on machine learning is proposed to inspect the defects of penicillin bottles. Scale Invariant Feature Transform (SIFT) is used to features extraction and a back propagation (BP) neural network classifier is employed to detect whether the bottles are with flaws. Experiments show that the proposed method is effective for penicillin bottle defects detection with high accuracy and fast speed.

The project was supported by the Opening Foundation of Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, China (TJUT-KLICNST-K20180002).

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Authors and Affiliations

  1. Tianjin University of Technology, Tianjin, 300384, People’s Republic of China

    Yangbo Feng & Shengyong Chen

  2. China Three Gorges University, Yichang, 443002, People’s Republic of China

    Tinglong Tang

  3. Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin, 300384, China

    Yangbo Feng, Tinglong Tang & Shengyong Chen

Authors
  1. Yangbo Feng
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  2. Tinglong Tang
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  3. Shengyong Chen
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Corresponding author

Correspondence to Yangbo Feng .

Editor information

Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Yongtian Wang

  2. University of Chinese Academy of Science, Beijing, China

    Qingmin Huang

  3. Institute of Computer Science and Technology, Peking University, Beijing, China

    Yuxin Peng

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Feng, Y., Tang, T., Chen, S. (2019). A Method of Penicillin Bottle Defect Inspection Based on BP Neural Network. In: Wang, Y., Huang, Q., Peng, Y. (eds) Image and Graphics Technologies and Applications. IGTA 2019. Communications in Computer and Information Science, vol 1043. Springer, Singapore. https://doi.org/10.1007/978-981-13-9917-6_4

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  • DOI: https://doi.org/10.1007/978-981-13-9917-6_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9916-9

  • Online ISBN: 978-981-13-9917-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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