Language:
English
繁體中文
Help
回圖書館首頁
手機版館藏查詢
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
A fuzzy approach to solve the stereo...
~
The University of Texas at El Paso., Electrical Eng.
Linked to FindBook
Google Book
Amazon
博客來
A fuzzy approach to solve the stereo correspondence problem using phase correlation.
Record Type:
Electronic resources : Monograph/item
Title/Author:
A fuzzy approach to solve the stereo correspondence problem using phase correlation./
Author:
Sanchez, Miguel Angel.
Description:
117 p.
Notes:
Adviser: Thompson Sarkodie-Gyan.
Contained By:
Masters Abstracts International46-06.
Subject:
Engineering, Electronics and Electrical. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1453847
ISBN:
9780549588603
A fuzzy approach to solve the stereo correspondence problem using phase correlation.
Sanchez, Miguel Angel.
A fuzzy approach to solve the stereo correspondence problem using phase correlation.
- 117 p.
Adviser: Thompson Sarkodie-Gyan.
Thesis (M.S.)--The University of Texas at El Paso, 2008.
This thesis presents a fuzzy logic approach using phase correlation to solve the correspondence problem in stereo vision. The stereo correspondence problem is one of the fundamental and classical problems in computer vision. It involves identifying equivalent pixels between images of a given stereo image pair. The displacement between these pixels results in a disparity map, which relates to depth information of the scene. Until recently, the performance of most solutions degrades significantly when there is a change in illumination between the two images. Moreover, a high computational cost is required for a better performance. The primary aim of the proposed work is to improve the performance between images with possible lighting variations, while maintaining a low computational cost, to solve the stereo correspondence problem. To compute the disparity at a given point, the phase correlation technique is applied to windows at different horizontal positions on the same vertical image line. Using these results, a fuzzy logic inference system selects the most similar window to compute the disparity at the given position. Eight stereo image pairs from a well-known database [6,28] are used to perform experiments (see appendix 1.2), as well as images taken with our set-up (see appendix 1.5). For the case of the database images, errors with respect to the ground truth disparity maps and computation time for different window sizes are shown. The images from our set-up are evaluated with respect to real object depths. Utilizing both type of images, database and ours, it is shown that the proposed solution performs well, while maintaining a low computational cost, in images with lighting variations.
ISBN: 9780549588603Subjects--Topical Terms:
626636
Engineering, Electronics and Electrical.
A fuzzy approach to solve the stereo correspondence problem using phase correlation.
LDR
:02704nmm 2200301 a 45
001
862723
005
20100721
008
100721s2008 ||||||||||||||||| ||eng d
020
$a
9780549588603
035
$a
(UMI)AAI1453847
035
$a
AAI1453847
040
$a
UMI
$c
UMI
100
1
$a
Sanchez, Miguel Angel.
$3
1030564
245
1 2
$a
A fuzzy approach to solve the stereo correspondence problem using phase correlation.
300
$a
117 p.
500
$a
Adviser: Thompson Sarkodie-Gyan.
500
$a
Source: Masters Abstracts International, Volume: 46-06, page: 3383.
502
$a
Thesis (M.S.)--The University of Texas at El Paso, 2008.
520
$a
This thesis presents a fuzzy logic approach using phase correlation to solve the correspondence problem in stereo vision. The stereo correspondence problem is one of the fundamental and classical problems in computer vision. It involves identifying equivalent pixels between images of a given stereo image pair. The displacement between these pixels results in a disparity map, which relates to depth information of the scene. Until recently, the performance of most solutions degrades significantly when there is a change in illumination between the two images. Moreover, a high computational cost is required for a better performance. The primary aim of the proposed work is to improve the performance between images with possible lighting variations, while maintaining a low computational cost, to solve the stereo correspondence problem. To compute the disparity at a given point, the phase correlation technique is applied to windows at different horizontal positions on the same vertical image line. Using these results, a fuzzy logic inference system selects the most similar window to compute the disparity at the given position. Eight stereo image pairs from a well-known database [6,28] are used to perform experiments (see appendix 1.2), as well as images taken with our set-up (see appendix 1.5). For the case of the database images, errors with respect to the ground truth disparity maps and computation time for different window sizes are shown. The images from our set-up are evaluated with respect to real object depths. Utilizing both type of images, database and ours, it is shown that the proposed solution performs well, while maintaining a low computational cost, in images with lighting variations.
590
$a
School code: 0459.
650
4
$a
Engineering, Electronics and Electrical.
$3
626636
650
4
$a
Engineering, Robotics.
$3
1018454
690
$a
0544
690
$a
0771
710
2
$a
The University of Texas at El Paso.
$b
Electrical Eng.
$3
1025819
773
0
$t
Masters Abstracts International
$g
46-06.
790
$a
0459
790
1 0
$a
Nava, Patricia
$e
committee member
790
1 0
$a
Sarkodie-Gyan, Thompson,
$e
advisor
790
1 0
$a
Tseng, Bill
$e
committee member
791
$a
M.S.
792
$a
2008
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1453847
based on 0 review(s)
Location:
全部
電子資源
Year:
Volume Number:
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
W9076103
電子資源
11.線上閱覽_V
電子書
EB W9076103
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login