Handwritten Numeric and Alphabetic Character Recognition and Signature Verification Using Neural Network

• 作者: Ahsan Habib Arafat Ullah Autish Chandra Moulik Md. Al Hasan Md. Atiqur Rahman Md. Badrul Alam Miah Md. Hasan Hasnain Nashif Md. Shariful Islam Mohammad Zakareya
• 来源期刊: 信息安全(英文)
• 学科: 工学
• 关键词: SIGNATURE Handwritten CHARACTER Image Processing FEATURE Extraction NEURAL Network RECOGNITION
• 年，卷（期）: 2018,（3）
• 页码范围: 209-224
• 页数: 16页
• 分类号: TP39

摘要

Handwritten signature and character recognition has become challenging research topic due to its numerous applications. In this paper, we proposed a system that has three sub-systems. The three subsystems focus on offline recognition of handwritten English alphabetic characters (uppercase and lowercase), numeric characters (0 - 9) and individual signatures respectively. The system includes several stages like image preprocessing, the post-processing, the segmentation, the detection of the required amount of the character and signature, feature extraction and finally Neural Network recognition. At first, the scanned image is filtered after conversion of the scanned image into a gray image. Then image cropping method is applied to detect the signature. Then an accurate recognition is ensured by post-processing the cropped images. MATLAB has been used to design the system. The subsystems are then tested for several samples and the results are found satisfactory at about 97% success rate. The quality of the image plays a vital role as the images of poor or mediocre quality may lead to unsuccessful recognition and verification.