An intelligent character recognition method to filter spam images on cloud
An intelligent character recognition method to filter spam images on cloud
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DOI：
10.1007/s00500-015-1811-5
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发表时间：
2015-07
期刊：
影响因子：
4.1
通讯作者：
Jun Chen;Hong Zhao;Jufeng Yang;Jian Zhang;Tao Li;Kai Wang
中科院分区：
文献类型：
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作者：
Jun Chen;Hong Zhao;Jufeng Yang;Jian Zhang;Tao Li;Kai Wang
近年来，云存储已成为数据共享的重要方式。数据所有者的数据保护和数据接收者的有害数据过滤是云存储中两个不可忽视的问题。云上的非法或不适当的消息会对未成年人产生负面影响，并且它们很容易转换为图像以避免基于文本的过滤。为了检测云端嵌入有害信息的垃圾邮件图像，需要软计算方法进行智能字符识别。 Dalal 和 Triggs 提出的 HOG 迄今为止已被证明是智能字符识别的最佳特征之一。当应用HOG识别整个单词时，总是使用预定义的滑动窗口来生成候选字符图像。然而，由于字符大小的差异，预定义窗口无法与每个字符完全匹配。待识别的字符图像通常会出现尺度变化和平移变化，这对智能字符识别的性能影响很大。为了解决这个问题，本文提出了HOG的扩展版本STRHOG。对两个公共数据集和一个我们的数据集的实验显示了我们工作的令人鼓舞的结果。改进的智能字符识别有助于过滤云端的垃圾图像。为了与其他方法进行公平比较，使用最近邻分类器进行智能字符识别。预计通过使用更好的分类器（例如模糊神经网络）可以进一步提高性能。
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.