Aniket Rawat,
Shivam Kudal,
Akshay Pawar,
Chirag Fulfagar,
Akshay Pawar,
Shalaka Deore,
- Student, Department of Computer Engineering, MES Wadia College of Engineering, S.P. Pune University. Pune, Maharashtra, India
- Student, Department of Computer Engineering, MES Wadia College of Engineering, S.P. Pune University. Pune, Maharashtra, India
- Student, Department of Computer Engineering, MES Wadia College of Engineering, S.P. Pune University. Pune, Maharashtra, India
- Student, Department of Computer Engineering, MES Wadia College of Engineering, S.P. Pune University. Pune, Maharashtra, India
- Student, Department of Computer Engineering, MES Wadia College of Engineering, S.P. Pune University. Pune, Maharashtra, India
- Student, Department of Computer Engineering, MES Wadia College of Engineering, S.P. Pune University. Pune, Maharashtra, India
Abstract
In creating a typical Optical Character Recognition (OCR) system, several steps are involved, such as preprocessing, segmentation, feature extraction, and classification. Preprocessing, which is a particularly interesting and challenging aspect of Document Analysis and Recognition (DAR), deals with converting scanned or photographed images containing machine-printed or handwritten text, including numbers, letters, and symbols, into a format that the system can understand. Segmentation is a crucial task in any OCR system, as it breaks down image text documents into lines, words, and characters. The accuracy of the OCR system heavily relies on the segmentation algorithm used. To handle significant degradation like cuts, blobs, merges, and vandalism, Google Cloud Vision is utilized to capture contextual relationships within the document. Moreover, the method seamlessly combines document restoration and super-resolution, making the process efficient and producing high-quality results directly from degraded documents. Through extensive testing on various document sources like magazines and books, significant improvements in image quality have been demonstrated. The approach is robust and adaptable, particularly excelling with severely degraded documents like books, making it an ideal solution for digital libraries and similar repositories aiming to preserve and enhance document collections.
Keywords: OCR, Google Cloud Vision, DAR, Feature Extraction, Digital Libraries
[This article belongs to Trends in Opto-electro & Optical Communication(toeoc)]
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Trends in Opto-electro & Optical Communication
| Volume | 14 |
| Issue | 02 |
| Received | July 24, 2024 |
| Accepted | July 31, 2024 |
| Published | August 17, 2024 |