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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 9
2867-2872,2880

Conditional generative adversarial network-based method for stepped surface highlight removal

Hu Yuhang1
Hu Haiyang1
Li Zhongjin1,2
1. College of Computer & Technology, Hangzhou Dianzi University, Hangzhou 310018, China
2. Intelligent Software Technology & Application Research Center, Advanced Institute of Information Technology, Peking University, Hangzhou 310000, China
DOI: 10.19734/j.issn.1001-3695.2022.02.0089

Abstract

It is difficult for traditional highlight removal algorithms to effectively deal with the processing of stepped highlight images in the stepped palletizing of factory robots. To solve this problem, based on the knowledge of conditional generative adversarial network, this paper proposed a stepped surface highlight removal network model named MSDGC-GAN. In this method, the SCFDB aimed to deeply extract the spatial background information between pixel rows and columns. In addition, the multi-scale gradient cascade structure aimed to compensate for the scale feature loss in network downsampling, and this structure could endow the model with multi-scale discriminative ability while stabilizing the training gradient distribution. Based on the analysis of the classical two-color reflectance model, this paper applied the maximum diffuse reflectance estimation to the loss function to supervise the network training. The experimental results show that the proposed method outperforms the compared methods in both the classical highlight dataset and the self-made stepped highlight image dataset.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.02.0089
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 9
Section: Technology of Graphic & Image
Pages: 2867-2872,2880
Serial Number: 1001-3695(2022)09-048-2867-06

Publish History

[2022-05-09] Accepted Paper
[2022-09-05] Printed Article

Cite This Article

胡宇航, 胡海洋, 李忠金. 基于条件生成对抗网络的梯级表面高光去除方法 [J]. 计算机应用研究, 2022, 39 (9): 2867-2872,2880. (Hu Yuhang, Hu Haiyang, Li Zhongjin. Conditional generative adversarial network-based method for stepped surface highlight removal [J]. Application Research of Computers, 2022, 39 (9): 2867-2872,2880. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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