{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T02:18:36Z","timestamp":1771467516949,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2012,1,5]],"date-time":"2012-01-05T00:00:00Z","timestamp":1325721600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Background subtraction is considered the first processing stage in video surveillance systems, and consists of determining objects in movement in a scene captured by a static camera. It is an intensive task with a high computational cost. This work proposes an embedded novel architecture on FPGA which is able to extract the background on resource-limited environments and offers low degradation (produced because of the hardware-friendly model modification). In addition, the original model is extended in order to detect shadows and improve the quality of the segmentation of the moving objects. We have analyzed the resource consumption and performance in Spartan3 Xilinx FPGAs and compared to others works available on the literature, showing that the current architecture is a good trade-off in terms of accuracy, performance and resources utilization. With less than a 65% of the resources utilization of a XC3SD3400 Spartan-3A low-cost family FPGA, the system achieves a frequency of 66.5 MHz reaching 32.8 fps with resolution 1,024 x 1,024 pixels, and an estimated power consumption of 5.76 W.<\/jats:p>","DOI":"10.3390\/s120100585","type":"journal-article","created":{"date-parts":[[2012,1,6]],"date-time":"2012-01-06T04:04:03Z","timestamp":1325822643000},"page":"585-611","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["FPGA Implementation for Real-Time Background Subtraction Based on Horprasert Model"],"prefix":"10.3390","volume":"12","author":[{"given":"Rafael","family":"Rodriguez-Gomez","sequence":"first","affiliation":[{"name":"Department of Computer Architecture and Technology, ETS Computer Engineering and Telecommunications, University of Granada, C\/ Periodista Daniel Saucedo s\/n, E18071 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enrique J.","family":"Fernandez-Sanchez","sequence":"additional","affiliation":[{"name":"Department of Computer Architecture and Technology, ETS Computer Engineering and Telecommunications, University of Granada, C\/ Periodista Daniel Saucedo s\/n, E18071 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Javier","family":"Diaz","sequence":"additional","affiliation":[{"name":"Department of Computer Architecture and Technology, ETS Computer Engineering and Telecommunications, University of Granada, C\/ Periodista Daniel Saucedo s\/n, E18071 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eduardo","family":"Ros","sequence":"additional","affiliation":[{"name":"Department of Computer Architecture and Technology, ETS Computer Engineering and Telecommunications, University of Granada, C\/ Periodista Daniel Saucedo s\/n, E18071 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2012,1,5]]},"reference":[{"key":"ref_1","unstructured":"Horprasert, T., Harwood, D., and Davis, L.S. (1999, January 21\u201321). A Statistical Approach for Real-Time Robust Background Subtraction and Shadow Detection. Kerkyra, Greece."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Karaman, M., Goldmann, L., Yu, D., and Sikora, T. (2005). Comparison of static background segmentation methods. Proc. SPIE, 5960.","DOI":"10.1117\/12.633437"},{"key":"ref_3","unstructured":"Stauffer, C., and Grimson, W.E.L. (1999, January 23\u201325). Adaptive Background Mixture Models for Real-Time Tracking. Fort Collins, CO, USA."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.3390\/s100201041","article-title":"A multiscale region-based motion detection and background subtraction algorithm","volume":"10","author":"Varcheie","year":"2010","journal-title":"Sensors"},{"key":"ref_5","unstructured":"Li, L., Huang, W., Gu, I.Y.H., and Tian, Q. (, January November). Foreground Object Detection from Videos Containing Complex Background. Berkeley, CA, USA."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.rti.2004.12.004","article-title":"Real-time foreground\/background segmentation using codebook model","volume":"11","author":"Kim","year":"2005","journal-title":"Real-Time Imaging"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"6092","DOI":"10.3390\/s100606092","article-title":"Background subtraction approach based on independent component analysis","volume":"10","year":"2010","journal-title":"Sensors"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"9232","DOI":"10.3390\/s101009232","article-title":"An intelligent architecture based on field programmable gate arrays designed to detect moving objects by using principal component analysis","volume":"10","author":"Bravo","year":"2010","journal-title":"Sensors"},{"key":"ref_9","unstructured":"Appiah, K., and Hunter, A. (2005, January 11\u201314). 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Canberra, ACT, Australia.","DOI":"10.1109\/DICTA.2008.77"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Pham, V., Vo, P., Hung, V.T., and Bac, L.H. (2010, January 1\u20134). GPU Implementation of Extended Gaussian Mixture Model for Background Subtraction. Hanoi, Vietnam.","DOI":"10.1109\/RIVF.2010.5634007"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"918","DOI":"10.1109\/TPAMI.2003.1206520","article-title":"Detecting moving shadows: Algorithms and evaluation","volume":"25","author":"Prati","year":"2003","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_16","unstructured":"Xilinx Available online: http:\/\/www.xilinx.com (accessed on 29 December 2011)."},{"key":"ref_17","unstructured":"Impulse accelerated technologies Available online: http:\/\/www.impulseaccelerated.com\/ (accessed on 29 December 2011)."},{"key":"ref_18","unstructured":"Seven Solutions S.L. 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