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RISS 인기검색어
- 검색키워드
- 저자 : Decai Sun (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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A Q-gram Filter for Local Alignment in Large Genomic Database
Decai Sun,Xiaoxia Wang 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.1
Fast and exact searching for sequences similar to a query sequence in genomic databases remains a challenging task in molecular biology. In this paper, the problem of finding all e-matches in a large genomic database is considered, i.e. all local alignments over a given length w and an error rate of at most e. A new database searching algorithm called QFLA is designed to solve this problem. The proposed algorithm is a full-sensitivity algorithm which is a refined q-gram filter and implemented on a q-gram index. First, new features are extracted from match-regions by logically partitioning both query sequence and genomic database. Second, a large part of irrelevant subsequences are eliminated quickly by these new features during the searching process. Last, the unfiltered regions are verified by the well-known smith-waterman algorithm. The experimental results demonstrate that our algorithm saves time by improving filtration efficiency in a short filtration time.
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Fingerprint Liveness Detection Using Gray Level Co-Occurrence Matrix Based Texture Feature
Chengsheng Yuan,Zhihua Xia,Xingming Sun,Decai Sun,Rui Lv 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.10
Fingerprint-based recognition systems have been widely deployed in numerous civilian and government applications. However, the fingerprint recognition systems can be deceived by using an accurate imitation of a real fingerprint such as an artificially made fingerprint. In this paper, we propose a novel software-based fingerprint liveness detection algorithm based on gray level co-occurrence matrix (GLCM), from which we can calculate the texture features of fingerprint images and obtain satisfactory results. For the first time, we extract texture features by constructing four-direction GLCMs in an image, and then quantization operation and normalization operation are adopted. After these, we detected whether a fingerprint image belongs to a real fingerprint or an artificial replica of it. A trained RBF SVM (support vector machine) classifiers scheme is used to make the final live/spoof decision via training and testing feature vectors. The experimental results reveal that our proposed method can discriminate between live fingerprints and fake ones with high classification accuracy.
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Fingerprint Liveness Detection Using Difference Co-occurrence Matrix Based Texture Features
Zhihua Xia,Chengsheng Yuan,Xingming Sun,Rui Lv,Decai Sun,Guangyong Gao 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.11
Fingerprint authentication systems have been widely deployed in both civilian and government applications, however, whether fingerprint authentication systems is security or not has been an important issue under fraudulent attempts through artificial spoof fingerprints. In this paper, inspired by popular feature descriptors such as gray level co-occurrence matrix (GLCM) and Gradient (difference matrix (DM)), we propose a novel software-based fingerprint liveness detection algorithm called difference co-occurrence matrix (DCM). In doing so, quantization operation is firstly conducted on the images. DMs are constructed by calculating difference matrices of horizontal and vertical pixel values of images; difference co-occurrence arrays are constructed from the difference matrices between adjacent pixels. To reduce the influence of abnormal pixel values, truncation is used for DMs. Then, we compute four parameters (Angular Second Moment, Entropy, Inverse Differential Moment and Correlation) used as feature vectors of fingerprint images. For the first time in the fingerprint liveness detection, we construct eight difference co-occurrence matrices and extract texture features from processed DCMs. Finally, SVM classifier is used to predict classification accuracy. The experimental results reveal that our proposed method can achieve more accurate classification compared with the best algorithms of 2013 Fingerprint Liveness Detection Competition, while being able to recognize spoofed fingerprints with a better degree of accuracy.
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Study of Spaceborne W-band Millimeter Wave Radiometer
Jing, Li,Shengwei, Zhang,Maohua, Sun,Decai, Kong,Heguang, Liu,Jingshan, Jiang 대한원격탐사학회 2001 International Symposium on Remote Sensing Vol.17 No.1
The W-band millimeter wave radiometer has been studied under the support of Chinese Academy of Science (CAS) and it is successfully studied for the first time in China. Its technical index is suitable for the use in space. The main characteristics of the W-band millimeter wave radiometer are introduced in this paper.
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