Differential Analysis of Modern Text Spotting Methods : A Systematic Review

Dr. Sheshang Degadwala; Riddhi Dave

doi:10.32628/CSEIT2410586

Authors

Dr. Sheshang Degadwala Professor & Head, Department of Computer Engineering, Sigma University, Vadodara, Gujarat, India Author
Riddhi Dave Research Scholar, Department of Computer Engineering, Sigma University, Vadodara, Gujarat, India Author

DOI:

https://doi.org/10.32628/CSEIT2410586

Keywords:

Text Spotting, Deep Learning, Scene Text Detection, Optical Character Recognition, end-to-end Frameworks, Machine Learning

Abstract

Text spotting, the task of detecting and recognizing text within images, is vital in applications like document analysis, autonomous navigation, and surveillance. The motivation for this review arises from the growing need for accurate automated text extraction methods, driven by the surge of visual data and the complexity of real-world environments. Despite advances in deep learning and computer vision, current text spotting techniques face significant challenges, including handling complex backgrounds, curved or distorted text, varied font styles, and low-resolution images. These limitations restrict their effectiveness in diverse, real-world settings. This systematic review aims to conduct a differential analysis of modern text spotting methods, highlighting their strengths, weaknesses, and performance in addressing such challenges. The objectives are to evaluate state-of-the-art techniques, identify gaps in the field, and propose future research directions. By critically synthesizing recent literature, this review provides insights that can help enhance the robustness and accuracy of text spotting systems, making them more adaptable to real-world conditions.

Downloads

Download data is not yet available.

References

Ghosh, Jyoti, et al. “A Light-Weight Natural Scene Text Detection and Recognition System.” Multimedia Tools and Applications, vol. 83, no. 3, 2024, pp. 6651–83, https://doi.org/10.1007/s11042-023-15696-0. DOI: https://doi.org/10.1007/s11042-023-15696-0

Bhavesh Kataria, "The Challenges of Utilizing Information Communication Technologies (ICTs) in Agriculture Extension, International Journal of Scientific Research in Science, Engineering and Technology, Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 1, pp.380-384, January-February-2015. Available at : https://doi.org/10.32628/ijsrset1511103 DOI: https://doi.org/10.32628/IJSRSET1511103

Hussein, Alaa, et al. “Deep Learning Techniques for Detecting and Segmenting Text in Natural Scene Images : Review.” Al-Nahrain Journal of Science, vol. 27, no. 2, 2024, pp. 133–44, https://doi.org/https://anjs.edu.iq/index.php/anjs/article/view/2752/2008. DOI: https://doi.org/10.22401/ANJS.27.2.14

Zhai, Yukun, et al. “TextFormer: A Query-Based End-to-End Text Spotter with Mixed Supervision.” Machine Intelligence Research, 2024, https://doi.org/10.1007/s11633-023-1460-6. DOI: https://doi.org/10.1007/s11633-023-1460-6

Nguyen, Nguyen, et al. “Efficiently Leveraging Linguistic Priors for Scene Text Spotting.” Computer Science, Linguistics, 2024, pp. 1–14, https://doi.org/10.48550/arXiv.2402.17134.

Liu, Yuliang, et al. “SPTS v2: Single-Point Scene Text Spotting.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 12, 2023, pp. 15665–79, https://doi.org/10.1109/TPAMI.2023.3312285. DOI: https://doi.org/10.1109/TPAMI.2023.3312285

Das, Alloy, et al. “Diving into the Depths of Spotting Text in Multi-Domain Noisy Scenes.” Computer Vision and Pattern Recognition, 2023, https://doi.org/10.48550/arXiv.2310.00558.

Da, Cheng, et al. “Multi-Granularity Prediction with Learnable Fusion for Scene Text Recognition.” European Computer Vision Association, 2023, pp. 1–18, http://arxiv.org/abs/2307.13244.

Zhao, Liang, et al. “CommuSpotter: Scene Text Spotting with Multi-Task Communication.” Applied Sciences (Switzerland), vol. 13, no. 23, 2023, https://doi.org/10.3390/app132312540. DOI: https://doi.org/10.3390/app132312540

Bhavesh Kataria, Dr. Harikrishna B. Jethva (2020). Sanskrit Character Recognition using Convolutional Neural Networks : A Survey. International Journal of Advanced Science and Technology, 29(7), 1059 – 1071, May 2020. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/15068

Liu, Yiyi, et al. “A Convolutional Recurrent Neural-Network-Based Machine Learning for Scene Text Recognition Application.” Symmetry, vol. 15, no. 4, 2023, https://doi.org/10.3390/sym15040849. DOI: https://doi.org/10.3390/sym15040849

Luan, Xin, et al. “Lightweight Scene Text Recognition Based on Transformer.” Sensors, vol. 23, no. 9, 2023, pp. 1–14, https://doi.org/10.3390/s23094490. DOI: https://doi.org/10.3390/s23094490

Zhang, Shiyu, et al. “Irregular Scene Text Detection Based on a Graph Convolutional Network.” Sensors, vol. 23, no. 3, 2023, pp. 1–17, https://doi.org/10.3390/s23031070. DOI: https://doi.org/10.3390/s23031070

Buoy, Rina, et al. “Explainable Connectionist-Temporal-Classification-Based Scene Text Recognition.” Journal of Imaging, vol. 9, no. 11, 2023, https://doi.org/10.3390/jimaging9110248. DOI: https://doi.org/10.3390/jimaging9110248

Lian, Zhe, et al. “PCBSNet: A Pure Convolutional Bilateral Segmentation Network for Real-Time Natural Scene Text Detection.” Electronics (Switzerland), vol. 12, no. 14, 2023, https://doi.org/10.3390/electronics12143055. DOI: https://doi.org/10.3390/electronics12143055

You, Yuwei, et al. “Arbitrary-Shaped Text Detection with B-Spline Curve Network.” Sensors, vol. 23, no. 5, 2023, pp. 1–13, https://doi.org/10.3390/s23052418. DOI: https://doi.org/10.3390/s23052418

Wu, Yirui, et al. “CDText: Scene Text Detector Based on Context-Aware Deformable Transformer.” Pattern Recognition Letters, vol. 172, 2023, pp. 8–14, https://doi.org/10.1016/j.patrec.2023.05.025. DOI: https://doi.org/10.1016/j.patrec.2023.05.025

Degadwala, S., et al. “Improvements in Diagnosing Kawasaki Disease Using Machine Learning Algorithms.” 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN), 2024, pp. 7–10, https://doi.org/10.1109/ICPCSN62568.2024.00009. DOI: https://doi.org/10.1109/ICPCSN62568.2024.00009

Mistry, S., and S. Degadwala. “Improved Multi-Type Vehicle Recognition with a Customized YOLO.” 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN), 2024, pp. 361–65, https://doi.org/10.1109/ICPCSN62568.2024.00063. DOI: https://doi.org/10.1109/ICPCSN62568.2024.00063

Patel, V., and S. Degadwala. “Deployment of 3D-Conv-LSTM for Precipitation Nowcast via Satellite Data.” 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN), 2024, pp. 984–88, https://doi.org/10.1109/ICPCSN62568.2024.00164. DOI: https://doi.org/10.1109/ICPCSN62568.2024.00164

Jagani, D., and S. Degadwala. “Monkeypox Skin Lesion Classification Using Fine-Tune CNN Model.” 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN), 2024, pp. 37–41, https://doi.org/10.1109/ICPCSN62568.2024.00014. DOI: https://doi.org/10.1109/ICPCSN62568.2024.00014

Degadwala, Sheshang, et al. “DeepSpine: Multi-Class Spine X-Ray Conditions Classification Using Deep Learning.” Proceedings - 2024 3rd International Conference on Sentiment Analysis and Deep Learning, ICSADL 2024, 2024, pp. 8–13, https://doi.org/10.1109/ICSADL61749.2024.00008. DOI: https://doi.org/10.1109/ICSADL61749.2024.00008

Gadhiya, Niravkumar, et al. “Novel Approach for Data Encryption with Multilevel Compressive.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 1368–72, https://doi.org/10.1109/ICICT60155.2024.10544502. DOI: https://doi.org/10.1109/ICICT60155.2024.10544502

Krishnamurthy, Vinay Nagarad Dasavandi, et al. “Predicting Hydrogen Fuel Cell Capacity Using Supervised Learning Models.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 1934–38, https://doi.org/10.1109/ICICT60155.2024.10544401. DOI: https://doi.org/10.1109/ICICT60155.2024.10544401

Gadhiya, Niravkumar, et al. “A Review on Different Level Data Encryption through a Compression Techniques.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 1378–81, https://doi.org/10.1109/ICICT60155.2024.10544803. DOI: https://doi.org/10.1109/ICICT60155.2024.10544803

Chakraborty, Utsho, et al. “Safeguarding Authenticity in Text with BERT-Powered Detection of AI-Generated Content.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 34–37, https://doi.org/10.1109/ICICT60155.2024.10544590. DOI: https://doi.org/10.1109/ICICT60155.2024.10544590

Bhavesh Kataria, Dr. Harikrishna B. Jethva, "CNN-Bidirectional LSTM Based Optical Character Recognition of Sanskrit Manuscripts : A Comprehensive Systematic Literature Review", International Journal of Scientific Research in Computer Science, Engineering and Information Technology , ISSN : 2456-3307, Volume 5, Issue 2, pp.1362-1383, March-April-2019. Available at doi : https://doi.org/10.32628/cseit2064126 DOI: https://doi.org/10.32628/CSEIT2064126

Prajapati, Piyush M., et al. “Exploring Methods of Mitigation against DDoS Attack in an IoT Network.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 1373–77, https://doi.org/10.1109/ICICT60155.2024.10544424. DOI: https://doi.org/10.1109/ICICT60155.2024.10544424

Agarwal, Ruhi Himanshu, et al. “Predictive Modeling for Thyroid Disease Diagnosis Using Machine Learning.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 227–31, https://doi.org/10.1109/ICICT60155.2024.10544462. DOI: https://doi.org/10.1109/ICICT60155.2024.10544462

Soni, Deepika, et al. “Veterinary Medical Records Application Using AWS.” Proceedings - 2024 5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024, 2024, pp. 578–84, https://doi.org/10.1109/ICMCSI61536.2024.00091. DOI: https://doi.org/10.1109/ICMCSI61536.2024.00091

Degadwala, Sheshang, et al. “Unveiling Cholera Patterns through Machine Learning Regression for Precise Forecasting.” Proceedings - 2024 5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024, 2024, pp. 39–44, https://doi.org/10.1109/ICMCSI61536.2024.00012. DOI: https://doi.org/10.1109/ICMCSI61536.2024.00012

Pandya, D. D., et al. “Retraction: Diagnostic Criteria for Depression Based on Both Static and Dynamic Visual Features (IDCIoT 2023 - International Conference on Intelligent Data Communication Technologies and Internet of Things, Proceedings (2023) DOI: 10.1109/IDCIoT56793.2023.10053450).” IDCIoT 2023 - International Conference on Intelligent Data Communication Technologies and Internet of Things, Proceedings, 2023, p. 1, https://doi.org/10.1109/IDCIoT56793.2023.10554339. DOI: https://doi.org/10.1109/IDCIoT56793.2023.10053450

Mewada, Shubbh, et al. “Improved CAD Classification with Ensemble Classifier and Attribute Elimination.” Proceedings - 2023 3rd International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2023, 2023, pp. 238–43, https://doi.org/10.1109/ICUIS60567.2023.00048. DOI: https://doi.org/10.1109/ICUIS60567.2023.00048

Pandya, Darshanaben D., et al. “Advancements in Multiple Sclerosis Disease Classification Through Machine Learning.” Proceedings - 2023 3rd International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2023, 2023, pp. 64–69, https://doi.org/10.1109/ICUIS60567.2023.00019. DOI: https://doi.org/10.1109/ICUIS60567.2023.00019

Degadwala, Sheshang, et al. “Enhancing Fleet Management with ESP8266-Based IoT Sensors for Weight and Location Tracking.” 3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023 - Proceedings, 2023, pp. 13–17, https://doi.org/10.1109/ICIMIA60377.2023.10425949. DOI: https://doi.org/10.1109/ICIMIA60377.2023.10425949

Degadwala, Sheshang, et al. “Enhancing Mesothelioma Cancer Diagnosis through Ensemble Learning Techniques.” 3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023 - Proceedings, 2023, pp. 628–32, https://doi.org/10.1109/ICIMIA60377.2023.10425887. DOI: https://doi.org/10.1109/ICIMIA60377.2023.10425887

Degadwala, Sheshang, et al. “Methods of Transfer Learning for Multiclass Hair Disease Categorization.” 2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023 - Proceedings, 2023, pp. 612–16, https://doi.org/10.1109/ICACRS58579.2023.10404492. DOI: https://doi.org/10.1109/ICACRS58579.2023.10404492

Degadwala, Sheshang, et al. “DeepTread: Exploring Transfer Learning in Tyre Quality Classification.” International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, 2023, pp. 1448–53, https://doi.org/10.1109/ICSCNA58489.2023.10370168. DOI: https://doi.org/10.1109/ICSCNA58489.2023.10370168

Mewada, Shubbh, et al. “Enhancing Raga Identification in Indian Classical Music with FCN-Based Models.” International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, 2023, pp. 980–85, https://doi.org/10.1109/ICSCNA58489.2023.10370046. DOI: https://doi.org/10.1109/ICSCNA58489.2023.10370046

Degadwala, Sheshang, et al. “Revolutionizing Hops Plant Disease Classification: Harnessing the Power of Transfer Learning.” International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, 2023, pp. 1706–11, https://doi.org/10.1109/ICSCNA58489.2023.10370692. DOI: https://doi.org/10.1109/ICSCNA58489.2023.10370692

Degadwala, Sheshang, et al. “Crime Pattern Analysis and Prediction Using Regression Models.” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, 2023, pp. 771–76, https://doi.org/10.1109/ICSSAS57918.2023.10331747. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331747

Bhavesh Kataria, Dr. Harikrishna B. Jethva (2021). Optical Character Recognition of Sanskrit Manuscripts Using Convolution Neural Networks, Webology, ISSN: 1735-188X, Volume 18 Issue 5, October-2021, pp. 403-424. Available at https://www.webology.org/abstract.php?id=1681

Prajapati, Rohit, et al. “QoS Based Virtual Machine Consolidation for Energy Efficient and Economic Utilization of Cloud Resources.” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, 2023, pp. 951–57, https://doi.org/10.1109/ICSSAS57918.2023.10331674. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331674

Patel, Fagun, et al. “Recognition of Pistachio Species with Transfer Learning Models.” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, 2023, pp. 250–55, https://doi.org/10.1109/ICSSAS57918.2023.10331907. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331907

Patel, Fagun, et al. “Exploring Transfer Learning Models for Multi-Class Classification of Infected Date Palm Leaves.” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, 2023, pp. 307–12, https://doi.org/10.1109/ICSSAS57918.2023.10331746. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331746

Pandya, Darshanaben D., et al. “Advancing Erythemato-Squamous Disease Classification with Multi-Class Machine Learning.” 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, 2023, pp. 542–47, https://doi.org/10.1109/I-SMAC58438.2023.10290599. DOI: https://doi.org/10.1109/I-SMAC58438.2023.10290599

Degadwala, Sheshang, et al. “Determine the Degree of Malignancy in Breast Cancer Using Machine Learning.” 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, 2023, pp. 483–87, https://doi.org/10.1109/I-SMAC58438.2023.10290430. DOI: https://doi.org/10.1109/I-SMAC58438.2023.10290430

Pandya, Darshanaben D., et al. “Unveiling the Power of Collective Intelligence: A Voting-Based Approach for Dementia Classification.” 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, 2023, pp. 478–82, https://doi.org/10.1109/I-SMAC58438.2023.10290165. DOI: https://doi.org/10.1109/I-SMAC58438.2023.10290165

Patel, Ankur, et al. “Enhancing Traffic Management with YOLOv5-Based Ambulance Tracking System.” Canadian Conference on Electrical and Computer Engineering, vol. 2023-September, 2023, pp. 528–32, https://doi.org/10.1109/CCECE58730.2023.10288751. DOI: https://doi.org/10.1109/CCECE58730.2023.10288751

Degadwala, Sheshang, et al. “Revolutionizing Prostate Cancer Diagnosis: Harnessing the Potential of Transfer Learning for MRI-Based Classification.” Proceedings of the 4th International Conference on Smart Electronics and Communication, ICOSEC 2023, 2023, pp. 938–43, https://doi.org/10.1109/ICOSEC58147.2023.10275879. DOI: https://doi.org/10.1109/ICOSEC58147.2023.10275879

Patel, Krunal, et al. “Safety Helmet Detection Using YOLO V8.” Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, 2023, pp. 22–26, https://doi.org/10.1109/ICPCSN58827.2023.00012. DOI: https://doi.org/10.1109/ICPCSN58827.2023.00012

Mehta, Jay N., et al. “EEG Brainwave Data Classification of a Confused Student Using Moving Average Feature.” Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, 2023, pp. 1461–66, https://doi.org/10.1109/ICPCSN58827.2023.00243. DOI: https://doi.org/10.1109/ICPCSN58827.2023.00243

Pareek, Naveen Kumar, et al. “Prediction of CKD Using Expert System Fuzzy Logic & AI.” Proceedings of the 2023 2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023, 2023, pp. 103–08, https://doi.org/10.1109/ICAISS58487.2023.10250477. DOI: https://doi.org/10.1109/ICAISS58487.2023.10250477

Degadwala, Sheshang, et al. “Enhancing Prostate Cancer Diagnosis: Leveraging XGBoost for Accurate Classification.” Proceedings of the 2023 2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023, 2023, pp. 1776–81, https://doi.org/10.1109/ICAISS58487.2023.10250511. DOI: https://doi.org/10.1109/ICAISS58487.2023.10250511

Degadwala, Sheshang, et al. “Empowering Maxillofacial Diagnosis Through Transfer Learning Models.” Proceedings of the 5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023, 2023, pp. 728–32, https://doi.org/10.1109/ICIRCA57980.2023.10220830. DOI: https://doi.org/10.1109/ICIRCA57980.2023.10220830

Degadwala, Sheshang, et al. “Enhancing Alzheimer Stage Classification of MRI Images through Transfer Learning.” Proceedings of the 5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023, 2023, pp. 733–37, https://doi.org/10.1109/ICIRCA57980.2023.10220651. DOI: https://doi.org/10.1109/ICIRCA57980.2023.10220651

Degadwala, Sheshang, et al. “Optimizing Hindi Paragraph Summarization through PageRank Method.” Proceedings of the 2nd International Conference on Edge Computing and Applications, ICECAA 2023, 2023, pp. 504–09, https://doi.org/10.1109/ICECAA58104.2023.10212107. DOI: https://doi.org/10.1109/ICECAA58104.2023.10212107

Dasavandi Krishnamurthy, Vinay Nagarad, et al. “Forecasting Future Sea Level Rise: A Data-Driven Approach Using Climate Analysis.” Proceedings of the 2nd International Conference on Edge Computing and Applications, ICECAA 2023, 2023, pp. 646–51, https://doi.org/10.1109/ICECAA58104.2023.10212399. DOI: https://doi.org/10.1109/ICECAA58104.2023.10212399

Degadwala, Sheshang, et al. “Cancer Death Cases Forecasting Using Supervised Machine Learning.” 2023 4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023 - Proceedings, 2023, pp. 903–07, https://doi.org/10.1109/ICESC57686.2023.10193685. DOI: https://doi.org/10.1109/ICESC57686.2023.10193685