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Scale Space Mining Algorithm for Big Data Filial Culture Image Processing

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DOI: 10.38007/Proceedings.0000331


Shuangxiao Gou

Corresponding Author

Shuangxiao Gou


With the rapid development of technologies such as the Internet, cloud computing, Internet of Things and big data, as well as the proliferation of tens of thousands of network access points, mobile terminals and network applications, high-value big data has been generated. Cyberspace security brings unprecedented challenges. The image culture of the dutiful son is one of China's fine traditional culture, but it has gradually weakened in the modern era. The country is looking forward to the filial piety culture in the new media era, and the image with filial piety can maintain vitality. The transformation of reality and innovation has made filial piety a reality. Through filial image processing and vectorization, this paper performs word vectorization on word traffic corpus big data to realize intelligent detection of big data cross-site scripting attacks. Image processing methods are used for data acquisition, feature extraction and other data preprocessing. The experimental results show that the mining algorithm based on anisotropic wavelet filial culture image space can be used for hierarchical differential detection.


Big Data; Filial Culture Image; Image Processing; Scale Space Mining