語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Text Segmentation and Recognition fo...
~
Rajalingam, Mallikka.
Text Segmentation and Recognition for Enhanced Image Spam Detection = An Integrated Approach /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Text Segmentation and Recognition for Enhanced Image Spam Detection/ by Mallikka Rajalingam.
其他題名:
An Integrated Approach /
作者:
Rajalingam, Mallikka.
面頁冊數:
IX, 114 p. 31 illus., 23 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Computational Intelligence. -
電子資源:
https://doi.org/10.1007/978-3-030-53047-1
ISBN:
9783030530471
Text Segmentation and Recognition for Enhanced Image Spam Detection = An Integrated Approach /
Rajalingam, Mallikka.
Text Segmentation and Recognition for Enhanced Image Spam Detection
An Integrated Approach /[electronic resource] :by Mallikka Rajalingam. - 1st ed. 2021. - IX, 114 p. 31 illus., 23 illus. in color.online resource. - EAI/Springer Innovations in Communication and Computing,2522-8609. - EAI/Springer Innovations in Communication and Computing,.
Chapter 1. Introduction -- Chapter 2. Review of Literature -- Chapter 3. Methodology -- Chapter 4. Character Segmentation -- Chapter 5. Character Recognition -- Chapter 6. Classification/Feature Extraction Using SVM and KNN Classifier -- Chapter 7. Experimentation and Result discussion -- Chapter 8. Conclusion. .
This book discusses email spam detection and its challenges such as text classification and categorization. The book proposes an efficient spam detection technique that is a combination of Character Segmentation and Recognition and Classification (CSRC). The author describes how this can detect whether an email (text and image based) is a spam mail or not. The book presents four solutions: first, to extract the text character from the image by segmentation process which includes a combination of Discrete Wavelet Transform (DWT) and skew detection. Second, text characters are via text recognition and visual feature extraction approach which relies on contour analysis with improved Local Binary Pattern (LBP). Third, extracted text features are classified using improvised K-Nearest Neighbor search (KNN) and Support Vector Machine (SVM). Fourth, the performance of the proposed method is validated by the measure of metric named as sensitivity, specificity, precision, recall, F-measure, accuracy, error rate and correct rate. Presents solutions to email spam detection and discusses its challenges such as text classification and categorization; Analyzes the proposed techniques’ performance using precision, F-measure, recall and accuracy; Evaluates the limitations of the proposed research thereby recommending future research.
ISBN: 9783030530471
Standard No.: 10.1007/978-3-030-53047-1doiSubjects--Topical Terms:
768837
Computational Intelligence.
LC Class. No.: TK1-9971
Dewey Class. No.: 621.382
Text Segmentation and Recognition for Enhanced Image Spam Detection = An Integrated Approach /
LDR
:03113nam a22004095i 4500
001
1045897
003
DE-He213
005
20210812140905.0
007
cr nn 008mamaa
008
220103s2021 sz | s |||| 0|eng d
020
$a
9783030530471
$9
978-3-030-53047-1
024
7
$a
10.1007/978-3-030-53047-1
$2
doi
035
$a
978-3-030-53047-1
050
4
$a
TK1-9971
072
7
$a
TJK
$2
bicssc
072
7
$a
TEC041000
$2
bisacsh
072
7
$a
TJK
$2
thema
082
0 4
$a
621.382
$2
23
100
1
$a
Rajalingam, Mallikka.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1349360
245
1 0
$a
Text Segmentation and Recognition for Enhanced Image Spam Detection
$h
[electronic resource] :
$b
An Integrated Approach /
$c
by Mallikka Rajalingam.
250
$a
1st ed. 2021.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2021.
300
$a
IX, 114 p. 31 illus., 23 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
EAI/Springer Innovations in Communication and Computing,
$x
2522-8609
505
0
$a
Chapter 1. Introduction -- Chapter 2. Review of Literature -- Chapter 3. Methodology -- Chapter 4. Character Segmentation -- Chapter 5. Character Recognition -- Chapter 6. Classification/Feature Extraction Using SVM and KNN Classifier -- Chapter 7. Experimentation and Result discussion -- Chapter 8. Conclusion. .
520
$a
This book discusses email spam detection and its challenges such as text classification and categorization. The book proposes an efficient spam detection technique that is a combination of Character Segmentation and Recognition and Classification (CSRC). The author describes how this can detect whether an email (text and image based) is a spam mail or not. The book presents four solutions: first, to extract the text character from the image by segmentation process which includes a combination of Discrete Wavelet Transform (DWT) and skew detection. Second, text characters are via text recognition and visual feature extraction approach which relies on contour analysis with improved Local Binary Pattern (LBP). Third, extracted text features are classified using improvised K-Nearest Neighbor search (KNN) and Support Vector Machine (SVM). Fourth, the performance of the proposed method is validated by the measure of metric named as sensitivity, specificity, precision, recall, F-measure, accuracy, error rate and correct rate. Presents solutions to email spam detection and discusses its challenges such as text classification and categorization; Analyzes the proposed techniques’ performance using precision, F-measure, recall and accuracy; Evaluates the limitations of the proposed research thereby recommending future research.
650
2 4
$a
Computational Intelligence.
$3
768837
650
2 4
$a
Computer Imaging, Vision, Pattern Recognition and Graphics.
$3
671334
650
1 4
$a
Communications Engineering, Networks.
$3
669809
650
0
$a
Algorithms.
$3
527865
650
0
$a
Computational intelligence.
$3
568984
650
0
$a
Optical data processing.
$3
639187
650
0
$a
Electrical engineering.
$3
596380
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783030530464
776
0 8
$i
Printed edition:
$z
9783030530488
776
0 8
$i
Printed edition:
$z
9783030530495
830
0
$a
EAI/Springer Innovations in Communication and Computing,
$x
2522-8595
$3
1288259
856
4 0
$u
https://doi.org/10.1007/978-3-030-53047-1
912
$a
ZDB-2-ENG
912
$a
ZDB-2-SXE
950
$a
Engineering (SpringerNature-11647)
950
$a
Engineering (R0) (SpringerNature-43712)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入