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Small target recognition method on weak features

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Abstract

For real time tracking the moving small target under complex backgrounds, this paper will present a tracking algorithm and a recognition method for small target based on the fusion filtering of single frame and multiple frames. For a case that the moving small target is masked or submersed easily by other objects or noise in complex background, this paper will present an opening and closing transform algorithm to eliminate or weaken background and noise; present a competitive model with adaptive neural network of online learning for the puniness characteristics of moving small target, use its competitive active unit to extract the multidimensional characteristic parameter of small target; consequently, present a tracking recognition method for moving small target based on a complex background. In conclusion, the significant novelty is the small target recognition method proposed, including the eliminating noise method, extraction method for weak small features, establishment of prediction model of motion target state, recognition method for small target. These researches development in this paper help to the personnel of target recognition and image processing understand the motion law, reduce expenditure, decrease unnecessary damage or injury, etc.

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Acknowledgments

This work is supported by Center Plain Science and Technology Innovation Talents (194200510016); Science and Technology Innovation Team Project of Henan Province University (19IRTSTHN013); The Fourth Intelligent Compilation Zhengzhou 1125 Science and Technology Innovation Talents (192101059006); Key Science and Technology Program of Henan Province (172102310447); Key Science Projects of Henan Universities (19A120004), respectively.

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China

    QingE Wu, Ziming An, Hu Chen & Xiaoliang Qian

  2. Key Laboratory of Grain Information Processing and Control, Ministry of Education, Henan University of Technology, Zhengzhou, 450001, China

    Lijun Sun

  3. Zhengzhou Key Laboratory of Machine Perception and Intelligent System, Henan University of Technology, Zhengzhou, 450001, China

    Lijun Sun

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  1. QingE Wu
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  2. Ziming An
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  3. Hu Chen
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  4. Xiaoliang Qian
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  5. Lijun Sun
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Correspondence to QingE Wu.

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Wu, Q., An, Z., Chen, H. et al. Small target recognition method on weak features. Multimed Tools Appl 80, 4183–4201 (2021). https://doi.org/10.1007/s11042-020-09926-y

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