Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (7): 213-218.doi: 10.11896/jsjkx.200800127

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Low Light Image Fusion Detection Method Based on Lego Filter and SSD

LI Lin1, LIU Xue-liang1, ZHAO Ye1, JI Ping2   

  1. 1 School of Computer and Information Engineering,Hefei University of Technology,Hefei 230601,China
    2 Department of Electronic Information and Electrical Engineering,Hefei University,Hefei 230601,China
  • Received:2020-08-19 Revised:2020-10-02 Online:2021-07-15 Published:2021-07-02
  • About author:LI Lin,born in 1994,postgraduate.Her main research interests include object detection and computer vision.(804082803@qq.com)
    LIU Xue-liang,born in 1981,Ph.D,associate professor,is a member of China Computer Federation.His main research interests include multimedia information retrieval and so on.
  • Supported by:
    Key R&D plan of the Ministry of Science and Technology(2018AAA0102002),National Natural Science Foundation of China(61976076,61632007,61932009,61806066) and Natural Science Research Projects of Universities in Anhui Province(KJ2018A0545).

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Abstract: Aiming at the problem that target detection is prone to misdetection or missing detection due to the complex background environment of low light image,this paper proposes a method to improve the accuracy and speed of low light image based on SSD object detection.Firstly,the low light image is enhanced,the processed enhanced image and the original low light image are respectively input into the SSD network structure with Lego filter for training detection.The two detection models are used to train and detect the enhanced data set,and a series of candidate frames are obtained.Finally,the non-repeated frames in the candidate frames are fused to mark the target in the correct position,so as to improve the detection accuracy of low light image.At the same time,Lego filter is integrated into the network structure to reduce the model parameters of network training,so as to improve the detection speed.Experimental results show that,when Lego filter is integrated in different positions of the network structure,the parameters of the model reduce by 8.9% and 29.5%,and the numbers of floating-point operations reduce by 6.8% and 34.9%.After fusion processing,the detection accuracy improves by 3% ~7%.This method is more suitable for practical application,effectively improves the detection speed and accuracy of low light image,and expands the application range of object detection.

Key words: Fusio, Lego filter, Low light image, Object detection, Single Shot MultiBox Detector algorithm

CLC Number: 

  • TP391
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