Text Segmentation and Recognition for Enhanced Image Spam Detection: An Integrated Approach

Text Segmentation and Recognition for Enhanced Image Spam Detection: An Integrated Approach Mallikka Rajalingam
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. Categories:
Computers – Computer Science
Year:
2021
Edition:
1st ed.
Publisher:
Springer International Publishing;Springer
Language:
english
Pages:
120
ISBN 10:
3030530477
ISBN 13:
9783030530471
Series:
EAI/Springer Innovations in Communication and Computing
File:
26 MB