Detection and identification of un-uniformed shape text from blurred video frames
- Title
- Detection and identification of un-uniformed shape text from blurred video frames
- Creator
- Channegowda R.H.; Srinivasaiah R.; Jankatti S.K.; Meenakshi; Jinachandra N.S.; Hombegowda R.K.T.
- Description
- The identification and recognition of text from video frames have received a lot of attention recently, that makes many computer vision-based applications conceivable. In this study, we modify the picture mask and the original identification of the mask region convolution neural network and permit detection in three levels, including holistic, sequence, and at the level of pixels. To identify the texts and determine the text forms, semantics at the pixel and holistic levels can be used. With masking and detection, existences of the character and the word are separated and recognised. In addition, text detection using the results of 2-D feature space instance segmentation is done. Moreover, we explore text recognition using an attention-based optical character recognition (OCR) method with mask region convolution neural networks (R-CNN) to address and detect the problem of smaller and blurrier texts at the sequential level. Using attribute maps of the word occurrences in sequence to seq, the OCR method calculates the character sequence. At last, a fine-grained learning strategy is proposed to constructs models at word level using the annotated datasets, resulting in the training of a more precise and reliable model. The well-known benchmark datasets ICDAR 2013 and ICDAR 2015 are used to test our suggested methodology. 2024, Institute of Advanced Engineering and Science. All rights reserved.
- Source
- IAES International Journal of Artificial Intelligence, Vol-13, No. 4, pp. 4795-4805.
- Date
- 2024-01-01
- Publisher
- Institute of Advanced Engineering and Science
- Subject
- Deep neural networks; Optical character recognition; Region convolution neural networks; Region of interest; Text detection; Text recognition
- Coverage
- Channegowda R.H., Department of Electronics and Communication Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, India; Srinivasaiah R., Department of Computer Science and Engineering, CHRIST Deemed to be University, Bengaluru, India; Jankatti S.K., Department of Computer Science and Technology, Dayananda Sagar University, Bengaluru, India; Meenakshi, Department of Computer Science and Engineering, RNS Institute of Technology, Bengaluru, India; Jinachandra N.S., Department of Mechanical Engineering, CHRIST Deemed to be University, Bengaluru, India; Hombegowda R.K.T., Department of Electronics and Communication Engineering, Ghousia College of Engineering, Ramanagara, India
- Rights
- Restricted Access
- Relation
- ISSN: 20894872
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Channegowda R.H.; Srinivasaiah R.; Jankatti S.K.; Meenakshi; Jinachandra N.S.; Hombegowda R.K.T., “Detection and identification of un-uniformed shape text from blurred video frames,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/12642.