東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

A two-dimensional vision system usin...

Chen, Yong.

Linked to FindBook

Google Book

Amazon

博客來

A two-dimensional vision system using artificial neural networks.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A two-dimensional vision system using artificial neural networks./
Author:	Chen, Yong.
Description:	114 p.
Notes:	Source: Masters Abstracts International, Volume: 37-06, page: 1920.
Contained By:	Masters Abstracts International37-06.
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1395274
ISBN:	059935755X

A two-dimensional vision system using artificial neural networks.
Chen, Yong.

A two-dimensional vision system using artificial neural networks. - 114 p.

Source: Masters Abstracts International, Volume: 37-06, page: 1920.

Thesis (M.E.S.)--Lamar University - Beaumont, 1999.

This thesis presents a two-dimensional image recognition system that is invariant to geometrical transformations. Traditional image recognition systems are slow in image processing even with the fastest computer because of their sequential execution. Furthermore, these systems are limited by their low tolerance for distortions and absence of tolerance for scaling and rotation. However, the recent advances in neural modeling have enabled us to overcome these limitations. This thesis presents a two-dimensional vision system using Artificial Neural Networks, which is based on the back propagation training algorithm. It involves image preprocessing, networks training, and image recalling. This system provides invariance for translation, rotation, and scaling. The designed system demonstrated better tolerance for image distortion and faster speed in detection than the conventional systems. This system has been implemented with Microsoft Visual C++ 5.0 to run under Windows environment. The Windows application makes it possible to interface to the real-time and real-world images through devices such as frame grabbers and scanners.

ISBN: 059935755XSubjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

A two-dimensional vision system using artificial neural networks.
LDR:01914nmm 2200253 4500 001 1837191
005 20050429080549.5
008 130614s1999 eng d
020 $a 059935755X
035 $a (UnM)AAI1395274
035 $a AAI1395274
040 $a UnM $c UnM
100 1 $a Chen, Yong. $3 1017770
245 1 2 $a A two-dimensional vision system using artificial neural networks.
300 $a 114 p.
500 $a Source: Masters Abstracts International, Volume: 37-06, page: 1920.
502 $a Thesis (M.E.S.)--Lamar University - Beaumont, 1999.
520 $a This thesis presents a two-dimensional image recognition system that is invariant to geometrical transformations. Traditional image recognition systems are slow in image processing even with the fastest computer because of their sequential execution. Furthermore, these systems are limited by their low tolerance for distortions and absence of tolerance for scaling and rotation. However, the recent advances in neural modeling have enabled us to overcome these limitations. This thesis presents a two-dimensional vision system using Artificial Neural Networks, which is based on the back propagation training algorithm. It involves image preprocessing, networks training, and image recalling. This system provides invariance for translation, rotation, and scaling. The designed system demonstrated better tolerance for image distortion and faster speed in detection than the conventional systems. This system has been implemented with Microsoft Visual C++ 5.0 to run under Windows environment. The Windows application makes it possible to interface to the real-time and real-world images through devices such as frame grabbers and scanners.
590 $a School code: 0424.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Artificial Intelligence. $3 769149
690 $a 0544
690 $a 0800
710 2 0 $a Lamar University - Beaumont. $3 1020444
773 0 $t Masters Abstracts International $g 37-06.
790 $a 0424
791 $a M.E.S.
792 $a 1999
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1395274