Real-time Bengali and Chinese numeral signs recognition using contour matching

Rahaman, Muhammad Aminur; Jasim, Mahmood; Zhang, Tao; Ali, Md. Yousuf; Hasanuzzaman, Md.

doi:10.1109/robio.2015.7418937

Cited by 7 publications

(3 citation statements)

References 6 publications

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“…We implemented rotation testing cases with the systems Fig. 7: Comparative analysis of each system's accuracy for rotated images [5], [14]- [17] for testing their system. From the graph we identified that system [17] works poorly for rotated images.…”

Section: Test Case-1 Rotationmentioning

confidence: 99%

“…In the graph x-axis showing the number of sample and the yaxis showing the existing system accuracy according to the testing cases. We implemented different background testing cases with the systems [5], [14]- [17] for testing their system. From the graph we identified that system [14] works poorly for different background images.…”

Section: F Test Case-4 Backgroundmentioning

confidence: 99%

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An Automated Testing Framework for Gesture Recognition System using Dynamic Image Pattern Generation with Augmentation

Ashaduzzaman

Hasan

Islam

et al. 2021

GUB JOURNAL OF SCIENCE AND ENGINEERING

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In the field of information technology, the gesture recognition system plays a very essential role. As it has achieved vast importance, it is mandatory to test the recognition system to ensure the quality of the system by identifying the bugs in the software. In our research, we suggested a dynamic testing method for gesture recognition software. using dynamic image pattern generation with augmentation. The automated software testing framework is a set of processes to create new test cases for properly testing a image processing software. The research intention for generate automated testing cases by following a standard process which helps to increase the performance and efficiency of the gesture recognition system. We have built the framework to give proper testing and give result (accuracy and defect) for which gesture recognition system already in the market. our research, the team strongly following and adding two software testing standard. First one is ISO/IEC/IEEE/291129-3 to define the process for testing software. And the second one is ISO/IEC/IEEE/291129-5 to implement the techniques for software testing. We proposed this framework with major five parameters by noise, rotation, background, contrast, and scale. Which are the most use with every gesture recognition system. Our developed framework’s phase is used to generate new testing cases based on the existing gesture recognition system’s data. There are we work with five systems, commonly with the gesture recognition for experiments. We provide the testing report with total accuracy and defect by comparing existing well-known system’s data. At the final result, our system suggested an analysis report based on the testing result. And tell what are the improvement needs for the existing system to consider noised images or different scaled images to build a robust system. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 7, Dec 2020 P 42-50

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Section: Test Case-1 Rotationmentioning

confidence: 99%

Section: F Test Case-4 Backgroundmentioning

confidence: 99%

An Automated Testing Framework for Gesture Recognition System using Dynamic Image Pattern Generation with Augmentation

Ashaduzzaman

Hasan

Islam

et al. 2021

GUB JOURNAL OF SCIENCE AND ENGINEERING

Self Cite

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“…In [11], the authors also introduced an approach for detecting BdSL letters and digits which applies a fuzzy-logic based model and gridpattern analysis in real-time. In [12], the authors presented a real-time Bengali and Chinese numeral signs recognition system using contour matching. The system is trained and tested using a total of 2000 contour templates separately for both Bengali and Chinese numeral signs from 10 signers and achieved recognition accuracy of 95.80% and 95.90% with computational cost of 8.023 milliseconds per frame.…”

Section: A Existing Bdsl Detection Techniquesmentioning

confidence: 99%

Real Time Bangladeshi Sign Language Detection using Faster R-CNN

Hoque

Jubair

Islam

et al. 2018

2018 International Conference on Innovation in Engineering and Technology (ICIET)

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Bangladeshi Sign Language (BdSL) is a commonly used medium of communication for the hearing-impaired people in Bangladesh. Developing a real time system to detect these signs from images is a great challenge. In this paper, we present a technique to detect BdSL from images that performs in real time. Our method uses Convolutional Neural Network based object detection technique to detect the presence of signs in the image region and to recognize its class. For this purpose, we adopted Faster Region-based Convolutional Network approach and developed a dataset -BdSLImset -to train our system. Previous research works in detecting BdSL generally depend on external devices while most of the other vision-based techniques do not perform efficiently in real time. Our approach, however, is free from such limitations and the experimental results demonstrate that the proposed method successfully identifies and recognizes Bangladeshi signs in real time.

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