Customized mask region based convolutional neural networks for un-uniformed shape text detection and text recognition
- Title
- Customized mask region based convolutional neural networks for un-uniformed shape text detection and text recognition
- Creator
- Channegowda R.H.; Karthik P.; Srinivasaiah R.; Shivaraj M.
- Description
- In image scene, text contains high-level of important information that helps to analyze and consider the particular environment. In this paper, we adapt image mask and original identification of the mask region based convolutional neural networks (R-CNN) to allow recognition at 3 levels such as sequence, holistic and pixel-level semantics. Particularly, pixel and holistic level semantics can be utilized to recognize the texts and define the text shapes, respectively. Precisely, in mask and detection, we segment and recognize both character and word instances. Furthermore, we implement text detection through the outcome of instance segmentation on 2-D feature-space. Also, to tackle and identify the text issues of smaller and blurry texts, we consider text recognition by attention-based of optical character recognition (OCR) model with the mask R-CNN at sequential level. The OCR module is used to estimate character sequence through feature maps of the word instances in sequence to sequence. Finally, we proposed a fine-grained learning technique that trains a more accurate and robust model by learning models from the annotated datasets at the word level. Our proposed approach is evaluated on popular benchmark dataset ICDAR 2013 and ICDAR 2015. 2023 Institute of Advanced Engineering and Science. All rights reserved.
- Source
- International Journal of Electrical and Computer Engineering, Vol-13, No. 1, pp. 413-424.
- Date
- 2023-01-01
- Publisher
- Institute of Advanced Engineering and Science
- Subject
- Deep neural networks; Optical character-recognition; Region based convolutional neural networks; Region of interest; Text detection; Text recognition
- Coverage
- Channegowda R.H., Department of Electronics and Communication Engineering, K S School of Engineering and Management, Ghousia College of Engineering, Visvesvaraya Technological University, Karnataka, India; Karthik P., Department of Electronics and Communication Engineering, K S School of Engineering and Management, Visvesvaraya Technological University, Karnataka, India; Srinivasaiah R., Department of Computer science and Engineering, Christ Deemed to be University, Karnataka, Bengaluru, India; Shivaraj M., Department of Electronics and Communication Engineering, Ghousia College of Engineering, Visvesvaraya Technological University, Ramanagaram, Karnataka, India
- Rights
- All Open Access; Gold Open Access; Green Open Access
- Relation
- ISSN: 20888708
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Channegowda R.H.; Karthik P.; Srinivasaiah R.; Shivaraj M., “Customized mask region based convolutional neural networks for un-uniformed shape text detection and text recognition,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/14434.