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

Edge detection methods based on gene...

Gonzalez, Claudia I.

FindBook

Google Book

Amazon

博客來

Edge detection methods based on generalized type-2 fuzzy logic

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Edge detection methods based on generalized type-2 fuzzy logic/ by Claudia I. Gonzalez ... [et al.].
其他作者:	Gonzalez, Claudia I.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	x, 89 p. :ill., digital ;24 cm.
內容註:	Introduction -- Generalized Type-2 Fuzzy Logic -- Edge Detection Methods and Filters Used on Digital Image Processing -- Metrics for Edge Detection Methods -- Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic Systems -- Generalized Type-2 Fuzzy Edge Detection Applied on a Face Recognition System -- Experimentation and Results Discussion -- Conclusions.
Contained By:	Springer eBooks
標題:	Computer vision - Mathematics. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-53994-2
ISBN:	9783319539942

Edge detection methods based on generalized type-2 fuzzy logic
Edge detection methods based on generalized type-2 fuzzy logic[electronic resource] /by Claudia I. Gonzalez ... [et al.]. - Cham :Springer International Publishing :2017. - x, 89 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology,2191-530X. - SpringerBriefs in applied sciences and technology..

Introduction -- Generalized Type-2 Fuzzy Logic -- Edge Detection Methods and Filters Used on Digital Image Processing -- Metrics for Edge Detection Methods -- Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic Systems -- Generalized Type-2 Fuzzy Edge Detection Applied on a Face Recognition System -- Experimentation and Results Discussion -- Conclusions.

In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra-dient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel operator; in the third approach the me-thodology based on Sobel operator and GT2 FSs is improved to be applied on color images. In the fourth approach, we proposed a novel edge detec-tion method where, a digital image is converted a generalized type-2 fuzzy image. In this book it is also included a comparative study of type-1, inter-val type-2 and generalized type-2 fuzzy systems as tools to enhance edge detection in digital images when used in conjunction with the morphologi-cal gradient and the Sobel operator. The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format. Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preprocessing phase of a face rec-ognition system; where the recognition system is based on a monolithic neural network. The aim of this part of the book is to show the advantage of using a generalized type-2 fuzzy edge detector in pattern recognition applications. The main goal of using generalized type-2 fuzzy logic in edge detec-tion applications is to provide them with the ability to handle uncertainty in processing real world images; otherwise, to demonstrate that a GT2 FS has a better performance than the edge detection methods based on type-1 and type-2 fuzzy logic systems.

ISBN: 9783319539942

Standard No.: 10.1007/978-3-319-53994-2doiSubjects--Topical Terms:

596840
Computer vision
--Mathematics.

LC Class. No.: TA1637

Dewey Class. No.: 006.42

Edge detection methods based on generalized type-2 fuzzy logic
LDR:02989nmm a2200325 a 4500 001 2092854
003 DE-He213
005 20170914142359.0
006 m d
007 cr nn 008maaau
008 171117s2017 gw s 0 eng d
020 $a 9783319539942 $q (electronic bk.)
020 $a 9783319539935 $q (paper)
024 7 $a 10.1007/978-3-319-53994-2 $2 doi
035 $a 978-3-319-53994-2
040 $a GP $c GP
041 0 $a eng
050 4 $a TA1637
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.42 $2 23
090 $a TA1637 $b .E23 2017
245 0 0 $a Edge detection methods based on generalized type-2 fuzzy logic $h [electronic resource] / $c by Claudia I. Gonzalez ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a x, 89 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in applied sciences and technology, $x 2191-530X
505 0 $a Introduction -- Generalized Type-2 Fuzzy Logic -- Edge Detection Methods and Filters Used on Digital Image Processing -- Metrics for Edge Detection Methods -- Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic Systems -- Generalized Type-2 Fuzzy Edge Detection Applied on a Face Recognition System -- Experimentation and Results Discussion -- Conclusions.
520 $a In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra-dient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel operator; in the third approach the me-thodology based on Sobel operator and GT2 FSs is improved to be applied on color images. In the fourth approach, we proposed a novel edge detec-tion method where, a digital image is converted a generalized type-2 fuzzy image. In this book it is also included a comparative study of type-1, inter-val type-2 and generalized type-2 fuzzy systems as tools to enhance edge detection in digital images when used in conjunction with the morphologi-cal gradient and the Sobel operator. The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format. Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preprocessing phase of a face rec-ognition system; where the recognition system is based on a monolithic neural network. The aim of this part of the book is to show the advantage of using a generalized type-2 fuzzy edge detector in pattern recognition applications. The main goal of using generalized type-2 fuzzy logic in edge detec-tion applications is to provide them with the ability to handle uncertainty in processing real world images; otherwise, to demonstrate that a GT2 FS has a better performance than the edge detection methods based on type-1 and type-2 fuzzy logic systems.
650 0 $a Computer vision $x Mathematics. $3 596840
650 0 $a Image processing. $3 621117
650 0 $a Fuzzy logic. $3 532071
650 0 $a Vision $x Computer simulation. $3 882368
650 1 4 $a Engineering. $3 586835
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Pattern Recognition. $3 891045
700 1 $a Gonzalez, Claudia I. $3 3227144
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in applied sciences and technology. $3 1565541
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-53994-2
950 $a Engineering (Springer-11647)