Arabic Handwritten Text for Person Biometric Identification: A Deep Learning Approach
This study thoroughly investigates how well deep learning models can recognize Arabic handwritten text for person biometric identification. It compares three advanced architectures -- ResNet50, MobileNetV2, and EfficientNetB7 -- using three widely recognized datasets: AHAWP, Khatt, and LAMIS-MSHD. Results show that EfficientNetB7 outperforms the others, achieving test accuracies of 98.57\%, 99.15\%, and 99.79\% on AHAWP, Khatt, and LAMIS-MSHD datasets, respectively. EfficientNetB7's exceptional performance is credited to its innovative techniques, including compound scaling, depth-wise separable convolutions, and squeeze-and-excitation blocks. These features allow the model to extract more abstract and distinctive features from handwritten text images. The study's findings hold significant implications for enhancing identity verification and authentication systems, highlighting the potential of deep learning in Arabic handwritten text recognition for person biometric identification.
Code (0)
등록된 구현이 없습니다.
Tasks
Deep LearningHandwritten Text RecognitionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition
We present the Manuscripts of Handwritten Arabic~(Muharaf) dataset, which is a machine learning dataset consisting of more than 1,600 historic handwritten page images transcribed by experts in archival Arabic. Each docum…
Handwritten Text RecognitionHTRBioTouchPass: Handwritten Passwords for Touchscreen Biometrics
This work enhances traditional authentication systems based on Personal Identification Numbers (PIN) and One-Time Passwords (OTP) through the incorporation of biometric information as a second level of user authenticatio…
Multi-Channel Time-Series Person and Soft-Biometric Identification
Multi-channel time-series datasets are popular in the context of human activity recognition (HAR). On-body device (OBD) recordings of human movements are often preferred for HAR applications not only for their reliabilit…
Activity RecognitionAttributeHuman Activity RecognitionPerson Identification+1Handwritten Arabic Character Recognition for Children Writ-ing Using Convolutional Neural Network and Stroke Identification
Automatic Arabic handwritten recognition is one of the recently studied problems in the field of Machine Learning. Unlike Latin languages, Arabic is a Semitic language that forms a harder challenge, especially with varia…
Activity-Biometrics: Person Identification from Daily Activities
In this work, we study a novel problem which focuses on person identification while performing daily activities. Learning biometric features from RGB videos is challenging due to spatio-temporal complexity and presence o…
Activity RecognitionDisentanglementPerson Identification