Text Segmentation and Recognition for Enhanced Image Spam Detection

An Integrated Approach

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Éditeur :

Springer


Collection :

EAI/Springer Innovations in Communication and Computing

Paru le : 2020-08-10



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Description
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.

Pages
114 pages
Collection
EAI/Springer Innovations in Communication and Computing
Parution
2020-08-10
Marque
Springer
EAN papier
9783030530464
EAN PDF
9783030530471

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
3359 Ko
Prix
105,49 €
EAN EPUB
9783030530471

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
14848 Ko
Prix
105,49 €