MATEC Web Conf.
Volume 140, 20172017 International Conference on Emerging Electronic Solutions for IoT (ICEESI 2017)
|Number of page(s)||5|
|Published online||11 December 2017|
Lossy Compression of Biometric Images Implemented Using Floating Point DSP Processor
School of Computer and Communication Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
2 School of Microelectronic Engineerig, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
* Corresponding author: email@example.com
In this paper, several numbers of biometric images are compressed in order to reduce the number of bits needed in representing an image with conservation of image quality. Biometric images compression is important to solve the problem of efficiently transmitting data and storing large number of biometric images in low capacity of memory device. Biometric images are compressed using two techniques which are DCT and Quantization. The compression algorithm is implemented on general purpose computer and DSP processor in order to compare between both of them in terms processing time and evaluate the performance of this technique by measuring the difference between the original image and reconstructed image using PSNR, SSIM and MSE. Experimental results show DCT algorithm produces a high quality for reconstructed images with acceptable compression rate in terms of quality level is more than 50%. Furthermore, implementing the proposed algorithm using DSP board achieves better performance in terms of processing time compared with PC based.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.