ScratchNet: Detecting the Scratches on Cellphone Screen

  • Zhao Luo
  • Xiaobing Xiao
  • Shiming GeEmail author
  • Qiting Ye
  • Shengwei Zhao
  • Xin Jin
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 773)


In the process of cellphone screen manufacture, equipment failures and human errors may lead to screen scratches. Traditional manual ways check scratches by human eyes, which often costs large manpower and time, but with poor effectiveness. To address this issue, we proposes an automated scratches detection method by cascading two main modules. First, the scratch filtering module detects big scratches and localizes small scratches candidates with a serial of low-level stages. Then, the scratches classification module applies a lightweight CNN model, ScratchNet, to identify each small scratch candidate whether it is real scratch or not. To train the ScratchNet, we build a Scratches on Cellphone Screen (SCS) dataset with 50K samples in 5 categories. The experimental results on SCS testing set show that the proposed method achieves an accuracy of \(96.35\%\) on classifying small scratches, which outperforms the LeNet model and the other classifiers.


Scratch detection Product quality inspection Cellphone screen Convolutional neural networks 



This work is supported in part by the National Key Research and Development Plan (Grant No. 2016YFC0801005), the National Natural Science Foundation of China (Grant No. 61402463) and Open Foundation Project of Robot Technology Used for Special Environment Key Laboratory of Sichuan Province in China (Grant No. 16kftk01).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Zhao Luo
    • 1
    • 2
  • Xiaobing Xiao
    • 3
  • Shiming Ge
    • 1
    • 2
    Email author
  • Qiting Ye
    • 1
    • 2
  • Shengwei Zhao
    • 1
    • 2
  • Xin Jin
    • 4
  1. 1.Institute of Information EngineeringChinese Academy of SciencesBeijingChina
  2. 2.School of Cyber SecurityUniversity of Chinese Academy of SciencesBeijingChina
  3. 3.School of Software and MicroelectronicsPeking UniversityBeijingChina
  4. 4.Department of Computer Science and TechnologyBeijing Electronic Science and Technology InstituteBeijingChina

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