Proceedings Article10.1109/IMSNA.2013.6743460
Image scaling algorithm based on GPU parallel processing
Chen Di,Xia Tian,Shen Yiying +2 more
- 01 Dec 2013
- pp 1044-1049
5
TL;DR: The method of third-order Lagrange interpolation, and GPU multi-thread parallel computing techniques is used to develop the speed of image scaling and simulation results show that the method presented can realize the fast scaling of mass-data image and the displaying effect is well.
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Abstract: With the technological advancements, the development of remote sensing is rapid, and the resolving capability of sensors has improved greatly, which makes that the further requirements have been raised for processing efficiency of mass-data image. Aim at the problem of the slow-footed processing of mass-data image, this paper modifies the method of third-order Lagrange interpolation, and GPU multi-thread parallel computing techniques is used to develop the speed of image scaling. The simulation results show that the method presented by this paper can realize the fast scaling of mass-data image and the displaying effect is well.
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Citations
Human Skin Colour Detection Algorithm Optimization with CUDA
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- 01 Aug 2017
TL;DR: This Human Skin Colour detection is analyzed to be a most suitable and strong cue for face detection and face recognition which finds various application in domain like surveillance, face biometrics, gesture recognition, interactive game application and many other.
1
GPU-based and Streaming-enabled Implementation of Pre-processing Flow towards Enhancing Optical Character Recognition Accuracy and Efficiency
29 Jun 2023
TL;DR: In this paper , the authors employed the Tesseract OCR and found that accuracy can be improved through preprocessing techniques including thresholding, rotation, rescaling, erosion, dilation, and noise removal, based on a dataset of 560 phone screen images.
GPGPU-based High Throughput Image Pre-processing Towards Large-Scale Optical Character Recognition
Serhan Gener,Parker Dattilo,Dhruv Gajaria,Alexander Fusco,Ali Akoglu +4 more
- 01 Dec 2022
TL;DR: This work leverages the open-source Tesseract OCR and shows that its accuracy can be improved through a pre-processing flow that includes thresholding, rotation, rescaling, erosion, dilation, and noise removal steps based on a dataset that is formed of 560 phone screen images.
GPGPU-based High Throughput Image Pre-processing Towards Large-Scale Optical Character Recognition
01 Dec 2022
TL;DR: In this paper , the authors leverage the Tesseract OCR and show that its accuracy can be improved through a preprocessing flow that includes thresholding, rotation, rescaling, erosion, dilation, and noise removal steps based on a dataset that is formed of 560 phone screen images.
Gpu-based and streaming-enabled implementation of pre-processing flow towards enhancing optical character recognition accuracy and efficiency
Gener Serhan,Dattilo Parker,Gajaria Dhruv,Fusco Alexander,Akoglu Ali +4 more
TL;DR: This study employed the open-source Tesseract OCR and found that accuracy can be improved through pre-processing techniques including thresholding, rotation, rescaling, erosion, dilation, and noise removal, based on a dataset of 560 phone screen images.
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