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An intelligent character recognition method to filter spam images on cloud

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Abstract

Cloud storage has become an important way for data sharing in recent years. Data protection for data owner and harmful data filtering for data recipients are two non-negligible problems in cloud storage. Illegal or unsuitable messages on cloud have a negative impact on minors and they are easily converted into images to avoid text-based filtering. To detect the spam image with the embedded harmful messages on cloud, soft computing methods are required for intelligent character recognition. HOG, proposed by Dalal and Triggs, has been demonstrated so far to be one of the best features for intelligent character recognition. A pre-defined sliding window is always used for the generation of candidate character images when HOG is applied to recognize the whole word. However, due to the difference in character sizes, the pre-defined window cannot exactly match with each character. Variations on scale and translation usually occur in the character image to be recognized, which have a great influence on the performance of intelligent character recognition. Aiming to solve this problem, STRHOG, an extended version of HOG, is proposed in this paper. Experiments on two public datasets and one our dataset have shown encouraging results for our work. The improved intelligent character recognition is helpful for filtering spam images on cloud. To make a fair comparison with other methods, nearest neighbor classifier is used for the intelligent character recognition. It is expected that the performance should be further improved by using better classifiers such as fuzzy neural network.

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Acknowledgments

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. This work is supported by the National Natural Science Foundation of China under Grant No. 61201424, 61301238, 61212005, the Tianjin Fundamental Research Funds under Grant No. 14JCTPJC00501, 14JCTPJC00556, and the Natural Science Foundation of Tianjin, China under Grant No. 12JCYBJC10100, 14ZCDZGX00831.

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Authors and Affiliations

  1. College of Computer and Control Engineering, Nankai University, Tianjin, People’s Republic of China

    Jun Chen, Hong Zhao, Jufeng Yang, Jian Zhang, Tao Li & Kai Wang

Authors
  1. Jun Chen
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  2. Hong Zhao
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  3. Jufeng Yang
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  4. Jian Zhang
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  5. Tao Li
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  6. Kai Wang
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Corresponding author

Correspondence to Kai Wang.

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Communicated by V. Loia.

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Chen, J., Zhao, H., Yang, J. et al. An intelligent character recognition method to filter spam images on cloud. Soft Comput 21, 753–763 (2017). https://doi.org/10.1007/s00500-015-1811-5

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