東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Orthogonal image moments for human-c...

Rahman, S. M. Mahbubur.

FindBook

Google Book

Amazon

博客來

Orthogonal image moments for human-centric visual pattern recognition

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Orthogonal image moments for human-centric visual pattern recognition/ by S. M. Mahbubur Rahman, Tamanna Howlader, Dimitrios Hatzinakos.
作者:	Rahman, S. M. Mahbubur.
其他作者:	Howlader, Tamanna.
出版者:	Singapore :Springer Singapore : : 2019.,
面頁冊數:	xii, 149 p. :ill. (some col.), digital ;24 cm.
內容註:	1 Introduction -- 2 Image Moments -- 3 Face Recognition -- 4 Expression Recognition -- 5 Fingerprint Classiﬁcation -- 6 Iris Recognition -- 7 Hand Gesture Recognition -- 8 Conclusion.
Contained By:	Springer eBooks
標題:	Pattern recognition systems. -
電子資源:	https://doi.org/10.1007/978-981-32-9945-0
ISBN:	9789813299450

Orthogonal image moments for human-centric visual pattern recognition
Rahman, S. M. Mahbubur.

Orthogonal image moments for human-centric visual pattern recognition[electronic resource] /by S. M. Mahbubur Rahman, Tamanna Howlader, Dimitrios Hatzinakos. - Singapore :Springer Singapore :2019. - xii, 149 p. :ill. (some col.), digital ;24 cm. - Cognitive intelligence and robotics,2520-1956. - Cognitive intelligence and robotics..

1 Introduction -- 2 Image Moments -- 3 Face Recognition -- 4 Expression Recognition -- 5 Fingerprint Classiﬁcation -- 6 Iris Recognition -- 7 Hand Gesture Recognition -- 8 Conclusion.

Instead of focusing on the mathematical properties of moments, this book is a compendium of research that demonstrates the effectiveness of orthogonal moment-based features in face recognition, expression recognition, fingerprint recognition and iris recognition. The usefulness of moments and their invariants in pattern recognition is well known. What is less well known is how orthogonal moments may be applied to specific problems in human-centric visual pattern recognition. Unlike previous books, this work highlights the fundamental issues involved in moment-based pattern recognition, from the selection of discriminative features in a high-dimensional setting, to addressing the question of how to classify a large number of patterns based on small training samples. In addition to offering new concepts that illustrate the use of statistical methods in addressing some of these issues, the book presents recent results and provides guidance on implementing the methods. Accordingly, it will be of interest to researchers and graduate students working in the broad areas of computer vision and visual pattern recognition.

ISBN: 9789813299450

Standard No.: 10.1007/978-981-32-9945-0doiSubjects--Topical Terms:

527885
Pattern recognition systems.

LC Class. No.: TK7882.P3 / R34 2019

Dewey Class. No.: 006.4

Orthogonal image moments for human-centric visual pattern recognition
LDR:02422nmm a2200337 a 4500 001 2218779
003 DE-He213
005 20191028151851.0
006 m d
007 cr nn 008maaau
008 201126s2019 si s 0 eng d
020 $a 9789813299450 $q (electronic bk.)
020 $a 9789813299443 $q (paper)
024 7 $a 10.1007/978-981-32-9945-0 $2 doi
035 $a 978-981-32-9945-0
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7882.P3 $b R34 2019
072 7 $a UYQV $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYQV $2 thema
082 0 4 $a 006.4 $2 23
090 $a TK7882.P3 $b R147 2019
100 1 $a Rahman, S. M. Mahbubur. $3 3453420
245 1 0 $a Orthogonal image moments for human-centric visual pattern recognition $h [electronic resource] / $c by S. M. Mahbubur Rahman, Tamanna Howlader, Dimitrios Hatzinakos.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a xii, 149 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Cognitive intelligence and robotics, $x 2520-1956
505 0 $a 1 Introduction -- 2 Image Moments -- 3 Face Recognition -- 4 Expression Recognition -- 5 Fingerprint Classiﬁcation -- 6 Iris Recognition -- 7 Hand Gesture Recognition -- 8 Conclusion.
520 $a Instead of focusing on the mathematical properties of moments, this book is a compendium of research that demonstrates the effectiveness of orthogonal moment-based features in face recognition, expression recognition, fingerprint recognition and iris recognition. The usefulness of moments and their invariants in pattern recognition is well known. What is less well known is how orthogonal moments may be applied to specific problems in human-centric visual pattern recognition. Unlike previous books, this work highlights the fundamental issues involved in moment-based pattern recognition, from the selection of discriminative features in a high-dimensional setting, to addressing the question of how to classify a large number of patterns based on small training samples. In addition to offering new concepts that illustrate the use of statistical methods in addressing some of these issues, the book presents recent results and provides guidance on implementing the methods. Accordingly, it will be of interest to researchers and graduate students working in the broad areas of computer vision and visual pattern recognition.
650 0 $a Pattern recognition systems. $3 527885
650 0 $a Computer vision. $3 540671
650 1 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
700 1 $a Howlader, Tamanna. $3 3453421
700 1 $a Hatzinakos, Dimitrios. $3 3453422
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Cognitive intelligence and robotics. $3 3338190
856 4 0 $u https://doi.org/10.1007/978-981-32-9945-0
950 $a Computer Science (Springer-11645)