DOCR-CAPTCHA: OCR Classifier based Deep Learning Technique for CAPTCHA Recognition

Mathew, Amal; Kulkarni, Apeksha; Antony, Anson; Bharadwaj, Shreeanant; Bhalerao, Swapnil

doi:10.1109/ocit53463.2021.00075

Cited by 1 publication

(1 citation statement)

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“…The domain of OCR in general scenarios, as delineated in the existing literature [24], encompasses a spectrum of tasks. These range from recognizing handwritten or printed documents to processing complex documents like invoices and bank statements, and even interpreting CAPTCHA systems [25,26]. Historically, early OCR techniques primarily focused on identifying individual characters or components, subsequently assembling them into words through the application of traditional computer vision approaches [18].…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

The Industrial Application of Artificial Intelligence-Based Optical Character Recognition in Modern Manufacturing Innovations

Tang,

Lee,

Jung

2024

Sustainability

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This paper presents the development of a comprehensive, on-site industrial Optical Character Recognition (OCR) system tailored for reading text on iron plates. Initially, the system utilizes a text region detection network to identify the text area, enabling camera adjustments along the x and y axes and zoom enhancements for clearer text imagery. Subsequently, the detected text region undergoes line-by-line division through a text segmentation network. Each line is then transformed into rectangular patches for character recognition by the text recognition network, comprising a vision-based text recognition model and a language network. The vision network performs preliminary recognition, followed by refinement through the language model. The OCR results are then converted into digital characters and recorded in the iron plate registration system. This paper’s contributions are threefold: (1) the design of a comprehensive, on-site industrial OCR system for autonomous registration of iron plates; (2) the development of a realistic synthetic image generation strategy and a robust data augmentation strategy to address data scarcity; and (3) demonstrated impressive experimental results, indicating potential for on-site industrial applications. The designed autonomous system enhances iron plate registration efficiency and significantly reduces factory time and labor costs.

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