Electronic Resource

Text Segmentation and Recognition for Enhanced Image Spam Detection

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
1908001141	EB0001747	006.6 Raj t	Central Library (OPAC)	Available

Detail Information

Series Title

-

Call Number

006.6 Raj t

Publisher

Switzerland : Springer Cham., 2020

Collation

ix, 114p.:Ill

Language

English

ISBN/ISSN

978-3-030-53047-1

Classification

006.6

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

1

Subject(s)

Pattern recognition systems

Specific Detail Info

-

Statement of Responsibility

BRF

Other version/related

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