Chen Liu, Benjamin Petroski, Guthrie Cordone, Gildo Torres, Stephanie Schuckers
Biometrics matching has been widely adopted as a secure way for identification and verification purpose. However, the computation demand associated with running this algorithm on a big data set poses great challenge on the underlying hardware platform. Even though modern processors are equipped with more cores and memory capacity, the software algorithm still requires careful […]
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Kritika Kurani
A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the person. Iris recognition systems are the most definitive biometric system since complex random iris patterns are unique to each individual and do not change with time. Iris Recognition is basically divided into three steps, namely, Iris […]
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T.A. Mahmoud Fayez
This work is an overview of a preliminary experience in developing high-performance face detection accelerated by GPU co-processors. The objective is to illustrate the advantages and difficulties encountered while utilizing the GPU technology to perform face detection. Moreover the introduced implementation is a much faster than currently existing techniques. Previous techniques for speeding up face […]
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M. Surumbarkhuzhali, P. Rachelin Sujae
Face recognition is the biometric identification of human’s face and matching the image against a library of known faces. The algorithm used to simulate the above is Eigen faces algorithm. The software which is been proposed to implement is Open CL. Open CL (Open Computing Language) is an open standard for general purpose parallel programming […]
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Indira Munagani
A fingerprint matching algorithm with a novel set of matching parameters based on core points and triangular descriptors is proposed to discover rarity in fingerprints. The algorithm uses a mathematical and statistical approach to discover rare features in fingerprints which provides scientific validation for both ten-print and latent fingerprint evidence. A feature is considered rare […]
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Shervin Rahimzadeh Arashloo, Josef Kittler
The paper addresses the problem of pose-invariant recognition of faces via an MRF matching model. Unlike previous costly matching approaches, the proposed algorithm employs effective techniques to reduce the MRF inference time. To this end, processing is done in a parallel fashion on a GPU employing a dual decomposition framework. The optimisation is further accelerated […]
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Abhishek Sinha
Iris recognition is quite a computation intensive task with huge amounts of pixel processing. After the image acquisition of the eye, Iris recognition is basically divided into Iris localization, Feature Extraction and Matching steps. Each of these tasks involves a lot of processing. It thus becomes essential to improve the performance of each step to […]
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Raja Lehtihet, Wael El Oraiby, Mohammed Benmohammed
This paper presents an optimized GPU (Graphics Processing Unit) implementation for fingerprint images enhancement using a Gabor filter-bank based algorithm. Given a batch of fingerprint images, we apply the Gabor filter bank and compute image variances of the convolution responses. We then select parts of these responses and compose the final enhanced batches. The algorithm […]
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Ali Ismail Awad
Driven from its uniqueness, immutability, acceptability, and low cost, fingerprint is in a forefront between biometric traits. Recently, the GPU has been considered as a promising parallel processing technology due to its high performance computing, commodity, and availability. Fingerprint authentication is keep growing, and includes the deployment of many image processing and computer vision algorithms. […]
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Youngsang Woo, Cheongyong Yi, Youngmin Yi
Face recognition is very important in many applications including surveillance, biometrics, and other domains. Fast face recognition is required if she wants to train or test more images or to increase the resolution of an input image for better accuracy in the recognition. Meanwhile, Graphics Processing Units (GPUs) have become widely available, offering the opportunity […]
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Tushar Mungle, Govardhan Hegde, Srikanth Prabhu, N.GopalaKrishna Kini
As we are in the development phase of our own super computer, we have identified several applications which are highly computationally intensive applications for a normal desktop computer to achieve the solution. These identified applications are related to multidisciplinary like bio-medical, mathematics, fluid dynamics, genetic algorithms. We are actually identifying the parallel computations involved in […]
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Brian C. Lovell, Abbas Bigdeli, Sandra Mau
The CCTV surveillance industry is undergoing a sea change due to the adoption of IP technologies. This is allowing the integration of a plethora of new cameras and other sensors into huge integrated networks. Adoption of IP technologies is presenting opportunities for scalable visual analytics that has the potential to add enormous value to entire […]
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Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

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Node 1
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  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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