2020 Vol.3 Apr. No.2

• Title: Research on efficient extraction algorithm of local fuzzy features of dynamic CT mechanical scanning image
• Name: Shao Yu
• Company: School of Electronic and Information Engineering
• Abstract:

  Aiming at the poor extraction effect of the current extraction algorithm for local fuzzy features of dynamic images and the low extraction accuracy, a new algorithm based on FAST corner is proposed to extract the local fuzzy feature of dynamic images efficiently. Through analyzing the mode distortion existing in the local fuzzy features of dynamic images, and processing the spatial domain of dynamic images by using point processing and neighborhood processing, and processing the image frequency domain by filtering, the preprocessing of dynamic images and the effect of local fuzzy feature extraction of dynamic images are improved. On the basis of this, aiming at the shortcomings of FAST corner extraction of local fuzzy features of dynamic images, this paper puts forward the idea of algorithm optimization, and analyzes the realization process of the improved algorithm to achieve the algorithm optimization processing and complete the local fuzzy feature extraction of dynamic images. Based on the least squares method, the inaccurate local fuzzy features in the dynamic images are removed to ensure the accuracy of feature extraction. Experimental results show that the proposed algorithm can accurately extract the local fuzzy features of dynamic images, and the extraction results are better.

• Keyword: dynamic images; local; fuzzy features; efficient extraction; algorithm research;
• DOI: 10.12250/jpciams2020020220
• Citation form: Shao Yu.Research on efficient extraction algorithm of local fuzzy features of dynamic CT mechanical scanning image[J]. Computer Informatization and Mechanical System, 2020, vol. 3, pp. 120-130.

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