Study on Cloud Image Processing and Analysis Based Flatfoot Classification Approach | Chapter 5 | Current Topics on Mathematics and Computer Science Vol. 5

This paper proposes a Cloud Image Processing and Analysis based Flatfoot Classification technique to aid doctors in detecting flat feet. Using image processing and analysis set up on separate virtual servers in the cloud, the suggested technique can reduce noise and shape images of the foot based on X-ray images. After image processing, the suggested division approach divides the individual X-ray image into four blocks, taking into account the fraction of each foot. By dividing the original image into four independent sub-partitions, different analysis techniques for key-point finding can be applied to each divided image. Each image can be processed using a cloud-based virtual machine. Using the proposed cloud-based algorithms for individual sub-partitions of the original image, the system can find four decision points for each block. Based on the integration of processing data from several methods, the system can detect flat feet automatically. The data and results of the identification might alternatively be submitted to a doctor for manual identification. The decision point can also be manually selected. To put it another way, based on the doctor's selection, the system can produce more accurate and objective findings. The simulation indicates that accuracy may be enhanced based on the dpi of the X-ray image. Furthermore, different strategies for determining decision points work differently.

Author (s) Details

Ming-Shen Jian
Department of Computer Science and Information Engineering, National Formosa University, Huwei, Yunlin, Taiwan, R.O.C.

Jun-Hong Shen
Department of Information Communication, Asia University, Wufeng, Taichung, Taiwan, R.O.C.

Yu-Chih Chen
Department of Computer Science and Information Engineering, National Formosa University, Huwei, Yunlin, Taiwan, R.O.C.

Chao-Chun Chang
Department of Computer Science and Information Engineering, National Formosa University, Huwei, Yunlin, Taiwan, R.O.C.

Yi-Chi Fang
Department of Computer Science and Information Engineering, National Formosa University, Huwei, Yunlin, Taiwan, R.O.C.

Ci-Cheng Chen
Department of Computer Science and Information Engineering, National Formosa University, Huwei, Yunlin, Taiwan, R.O.C.

Wei-Han Chen
Department of Computer Science and Information Engineering, National Formosa University, Huwei, Yunlin, Taiwan, R.O.C.

View Book :- https://stm.bookpi.org/CTMCS-V5/article/view/2432