Coin classification in a complex environment

Huanhuan Chang; Zhiqiang Wei; Lei Huang; Jie Nie; Wenfeng Zhang; Lu Wang

doi:10.1117/12.2524185

6 May 2019 Coin classification in a complex environment

Huanhuan Chang, Zhiqiang Wei, Lei Huang, Jie Nie, Wenfeng Zhang, Lu Wang

Proceedings Volume 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018); 110691K (2019) https://doi.org/10.1117/12.2524185
Event: Tenth International Conference on Graphic and Image Processing (ICGIP 2018), 2018, Chengdu, China

Abstract

Coin classification automatically plays important roles in many applications, e.g., vending systems. Glossy reflection is one of the key factor that affect the performance of vision-based coin classification, especially in a complex environment. In this paper, we propose a novel method for robust coin classification. Contrary to the previous method, we get the glossy area first. Edge features and texture features are used in glossy area detection. Then the deep learning features are extracted based on non-glossy area instead of the whole coin image. Finally, the coin classification results are got from the VGG nets scheme. Comprehensive experiments show that our method is robust under various complex environments. The comparison experiments demonstrate that our method can outperform the state-of-the-art method. Our method achieves 95.80% accuracy.

Citation Download Citation

Huanhuan Chang, Zhiqiang Wei, Lei Huang, Jie Nie, Wenfeng Zhang, and Lu Wang "Coin classification in a complex environment", Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 110691K (6 May 2019); https://doi.org/10.1117/12.2524185

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KEYWORDS

Image classification

Image segmentation

Edge detection

Feature extraction

Classification systems

Image processing

Reflection

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