• Title/Summary/Keyword: minutiae descriptor

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An Improved Cancelable Fingerprint Template Encryption System Research

  • Wang, Feng;Han, Bo;Niu, Lei;Wang, Ya
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.4
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    • pp.2237-2253
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    • 2017
  • For the existing security problem based on Fuzzy Vault algorithm, we propose a cancelable fingerprint template encryption scheme in this paper. The main idea is to firstly construct an irreversible transformation function, and then apply the function to transform the original template and template information is stored after conversion. Experimental results show it effectively prevents the attack from fingerprint template data and improves security of the system by using minutiae descriptor to encrypt abscissa of the vault. The experiment uses public FVC2004 fingerprint database to test, result shows that although the recognition rate of the proposed algorithm is slightly lower than the original program, but the improved algorithm security and complexity are better, and therefore the proposed algorithm is feasible in general.

Efficient Image Stitching Using Fast Feature Descriptor Extraction and Matching (빠른 특징점 기술자 추출 및 정합을 이용한 효율적인 이미지 스티칭 기법)

  • Rhee, Sang-Burm
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.1
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    • pp.65-70
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    • 2013
  • Recently, the field of computer vision has been actively researched through digital image which can be easily generated as the development and expansion of digital camera technology. Especially, research that extracts and utilizes the feature in image has been actively carried out. The image stitching is a method that creates the high resolution image using features extract and match. Image stitching can be widely used in military and medical purposes as well as in variety fields of real life. In this paper, we have proposed efficient image stitching method using fast feature descriptor extraction and matching based on SURF algorithm. It can be accurately, and quickly found matching point by reduction of dimension of feature descriptor. The feature descriptor is generated by classifying of unnecessary minutiae in extracted features. To reduce the computational time and efficient match feature, we have reduced dimension of the descriptor and expanded orientation window. In our results, the processing time of feature matching and image stitching are faster than previous algorithms, and also that method can make natural-looking stitched image.