Abstract
We present a novel dedicated hardware system for the extraction of second-order statistical features from high-resolution images. The selected features are based on gray level co-occurrence matrix analysis and are angular second moment, correlation, inverse difference moment and entropy. The proposed system was evaluated using input images with resolutions that range from 512(512 to 2048(2048 pixels. Each image is divided into blocks of user-defined size and a feature vector is extracted for each block. The system is implemented on a **linx VirtexE-2000 FPGA and uses integer arithmetic, a sparse co-occurrence matrix representation and a fast logarithm approximation to improve efficiency. It allows the parallel calculation of sixteen co-occurrence matrices and four feature vectors on the same FPGA core. The experimental results illustrate the feasibility of real-time feature extraction for input images of dimensions up to 2048(2048 pixels, where a performance of 32 images per second is achieved.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Karkanis, S.A., Iakovidis, D.K., Maroulis, D.E., Karras, D.A., Tzivras, M.: Computer Aided Tumor Detection in Endoscopic Video Using Color Wavelet Features. IEEE Trans. Inf. Technol. Biomed. 7, 141–152 (2003)
Tahir, M.A., Bouridane, A., Kurugollu, F.: An FPGA Based Coprocessor for GLCM and Haralick Texture Features and their Application in Prostate Cancer Classification. Anal. Int. Circ. Signal Process. 43, 205–215 (2005)
Baraldi, A., Parmiggiani, F.: An Investigation of the Textural Characteristics Associated with Gray Level Cooccurrence Matrix Statistical Parameters. IEEE Trans. Geosc. Rem. Sens. 33(2), 293–304 (1995)
Shiranita, K., Miyajima, T., Takiyama, R.: Determination of Meat Quality by Texture Analysis. Patt. Rec. Lett. 19, 1319–1324 (1998)
Iivarinen, J., Heikkinen, K., Rauhamaa, J., Vuorimaa, P., Visa, A.: A Defect Detection Scheme for Web Surface Inspection. Int. J. Pat. Rec. Artif. Intell., 735–755 (2000)
Haralick, R.M., Shanmugam, K., Dinstein, I.: Textural Features for Image Classification. IEEE Trans. Syst. Man Cybern. 3, 610–621 (1973)
Iakovidis, D.K., Maroulis, D.E., Karkanis, S.A., Flaounas, I.N.: Color Texture Recognition in Video Sequences Using Wavelet Covariance Features and Support Vector Machines. In: Proc. 29th EUROMICRO, Antalya, Turkey, September 2003, pp. 199–204 (2003)
Wei, C.-H., Li, C.-T., Wilson, R.: A Content-Based Approach to Medical Image Database Retrieval. In: Ma, Z. (ed.) Database Modeling for Industrial Data Management: Emerging Technologies and Applications. Idea Group Publishing, USA (2005)
York, T.A.: Survey of Field Programmable Logic Devices. Microprocessors and Microsystems 17(7), 371–381 (1993)
Ba, M., Degrugillier, D., Berrou, C.: Digital VLSI Using Parallel Architecture for Co-occurrence Matrix Determination. In: Proc. Int. Conf. on Acoustics, Speech, and Signal Proc., vol. 4, pp. 2556–2559 (1989)
Heikkinen, K., Vuorimaa, P.: Computation of Two Texture Features in Hardware. In: Proc. 10th Int. Conf. Image Analysis and Processing, Venice, Italy, September 1999, pp. 125–129 (1999)
Theodoridis, S., Koutroumbas, K.: Pattern Recognition. Academic Press, San Diego (1999)
Haralick, R.M.: Texture Measures for Carpet Wear Assessment. IEEE Trans. Pattern Analysis and Machine Intelligence 10(1), 92–104 (1988)
Hennesy, J.L., Patterson, D.A.: Computer Architecture, A Quantitative Approach. Morgan Kaufmann, San Francisco (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bariamis, D., Iakovidis, D.K., Maroulis, D. (2006). Dedicated Hardware for Real-Time Computation of Second-Order Statistical Features for High Resolution Images. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_7
Download citation
DOI: https://doi.org/10.1007/11864349_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44630-9
Online ISBN: 978-3-540-44632-3
eBook Packages: Computer ScienceComputer Science (R0)