Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Jeng-Horng Chang"'
Autor:
Jeng-Horng Chang, 張正弘
89
Ridges and ravines are the main components constituting a fingerprint. Traditional Automatic Fingerprint Identification Systems (AFIS) are mainly based on minutiae matching techniques. The minutiae for fingerprint identification are defined b
Ridges and ravines are the main components constituting a fingerprint. Traditional Automatic Fingerprint Identification Systems (AFIS) are mainly based on minutiae matching techniques. The minutiae for fingerprint identification are defined b
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/78873947177873333329
Publikováno v:
Future Generation Computer Systems. 20:1131-1143
In this paper, a novel filter-based greedy modular subspace (GMS) technique is proposed to improve the accuracy of high-dimensional data classification. The proposed approach initially divides the whole set of high-dimensional features into several a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8bffafef4ef203cd5e2c2ff9623d950f
https://doi.org/10.1016/j.future.2003.11.003
https://doi.org/10.1016/j.future.2003.11.003
Autor:
Jeng Horng Chang, Kuo Chin Fan
Publikováno v:
Pattern Recognition. 35:1209-1223
In this paper, a new method is introduced which is a combination of structural and syntactic approaches for fingerprint classification. The goal of the proposed ridge distribution (R-D) model is to present the idea of the possibility for classifying
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d505a35ff2da2d5e09f8832c88d87a7
https://doi.org/10.1016/s0031-3203(01)00121-2
https://doi.org/10.1016/s0031-3203(01)00121-2
Publikováno v:
Image and Vision Computing. 20:203-216
In this paper, we present a novel multi-modal histogram thresholding method in which no a priori knowledge about the number of clusters to be extracted is needed. The proposed method combines regularization and statistical approaches. By converting t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::379893a21455464fa3c091af6edc973f
https://doi.org/10.1016/s0262-8856(01)00095-6
https://doi.org/10.1016/s0262-8856(01)00095-6
Autor:
Kuo Chin Fan, Jeng Horng Chang
Publikováno v:
Pattern Recognition. 34:1907-1925
Ridges and ravines are the main components constituting a fingerprint. Traditional automatic fingerprint identification systems (AFIS) are based on minutiae matching techniques. The minutiae for fingerprint identification are defined by ridge termina
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc9dd85af0f693f69221cfe6b12da735
https://doi.org/10.1016/s0031-3203(00)00133-3
https://doi.org/10.1016/s0031-3203(00)00133-3
Autor:
Kun-Shan Chen, Chia Tang Chen, Kuo Chin Fan, Chin-Chuan Han, Yang-Lang Chang, Jeng Horng Chang
Publikováno v:
SPIE Proceedings.
High-dimensional spectral imageries obtained from multispectral, hyperspectral or even ultraspectral bands generally provide complementary characteristics and analyzable information. Synthesis of these data sets into a composite image containing such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::934ca8b08358cb4a7148e177def99a82
https://doi.org/10.1117/12.487468
https://doi.org/10.1117/12.487468
Publikováno v:
SPIE Proceedings.
In this paper, a novel filter-based greedy modular subspace (GMS)technique is proposed to improve the accuracy of high-dimensional remote sensing image supervisor classification. The approach initially divides the whole set of high-dimensional featur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bbc687d8f9031cceb2d4a33d506d720c
https://doi.org/10.1117/12.451532
https://doi.org/10.1117/12.451532
Autor:
Kun-Shan Chen, Jeng-Horng Chang, Kuo-Chin Fan, Chin-Chuan Han, Chia-Tang Chen, Yang-Lang Chang
Publikováno v:
Optical Engineering. 42:2576
This paper presents a new supervised classification tech- nique for hyperspectral imagery, which consists of two algorithms, re- ferred to as the greedy modular eigenspace (GME) and the positive Boolean function (PBF). The GME makes use of the data c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52a17f1e87c27b7c4ed136a13405a111
https://doi.org/10.1117/1.1593037
https://doi.org/10.1117/1.1593037