{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:44:00Z","timestamp":1781106240547,"version":"3.54.1"},"reference-count":26,"publisher":"IGI Global Scientific Publishing","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,4,1]]},"abstract":"<p>In this paper, the authors present an improved Artificial Bee Colony Algorithm (ABC) for the object recognition problem in complex digital images. The ABC is a new metaheuristics approach inspired by the collective foraging behavior of honey bee swarms. The objective is to find a pattern or reference image (template) of an object somewhere in a target landscape scene that may contain noise and changes in brightness and contrast. First, several search strategies were tested to find the most appropriate. Next, many experiments were done using complex digital grayscale and color images. Results are analyzed and compared with other algorithms through Pareto plots and graphs that show that the improved ABC was more efficient than the original ABC.<\/p>","DOI":"10.4018\/jncr.2010040104","type":"journal-article","created":{"date-parts":[[2010,9,7]],"date-time":"2010-09-07T19:09:05Z","timestamp":1283886545000},"page":"54-70","source":"Crossref","is-referenced-by-count":13,"title":["An Improved Artificial Bee Colony Algorithm for the Object Recognition Problem in Complex Digital Images Using Template Matching"],"prefix":"10.4018","volume":"1","author":[{"given":"Chidambaram","family":"Chidambaram","sequence":"first","affiliation":[{"name":"Federal Technological University of Paran\u00e1 (UTFPR) and Santa Catarina State University (UDESC), Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heitor Silv\u00e9rio","family":"Lopes","sequence":"additional","affiliation":[{"name":"Federal Technological University of Paran\u00e1 (UTFPR), Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jncr.2010040104-0","doi-asserted-by":"crossref","unstructured":"Bahamish, H. A. A., Abdullah, R. A., & Salam, R. A. (2008). Protein conformational search using bees algorithm. In Proceedings of the Second Asia International Conference on Modelling and Simulation (pp. 911-916).","DOI":"10.1109\/AMS.2008.65"},{"key":"jncr.2010040104-1","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780195131581.001.0001","author":"E.Bonabeau","year":"1999","journal-title":"Swarm Intelligence \u2013 From Natural to Artificial Systems"},{"key":"jncr.2010040104-2","doi-asserted-by":"publisher","DOI":"10.1002\/9780470744055"},{"key":"jncr.2010040104-3","unstructured":"Cole, L., Austin, D., & Cole, L. (2004). Visual object recognition using template matching. In Proceedings of the Autralasian Conference on Robotics & Automation. Retrieved September 20, 2009, from http:\/\/www.araa.asn.au\/acra\/acra2004"},{"key":"jncr.2010040104-4","doi-asserted-by":"crossref","unstructured":"Evans, H., & Zhang, M. (2008). Particle Swarm Optimisation for Object Classification. In Proceedings of the 23rd International Conference on Image and Vision Computing (pp. 1-6).","DOI":"10.1109\/IVCNZ.2008.4762143"},{"key":"jncr.2010040104-5","doi-asserted-by":"crossref","unstructured":"H\u00e4ckel, S., & Dippold, P. (2009). The bee colony-inspired algorithm (BCiA): a two-stage approach for solving the vehicle routing problem with time windows. In Proceedings of the 11th Genetic and Evolutionary Computation Conference (pp. 25-32).","DOI":"10.1145\/1569901.1569906"},{"key":"jncr.2010040104-6","first-page":"358","article-title":"Particle swarm optimization for the multidimensional knapsack problem (","volume":"4331","author":"F.Hembecker","year":"2007","journal-title":"LNCS"},{"key":"jncr.2010040104-7","doi-asserted-by":"publisher","DOI":"10.1007\/BF00176152"},{"key":"jncr.2010040104-8","unstructured":"Karaboga, D. (2005). An Idea Based on Honey Bee Swarm for Numerical optimization (Tech. Rep. No. TR06). Kayseri, Turkey: Erciyes University, Engineering Faculty, Computer Engineering Department."},{"key":"jncr.2010040104-9","doi-asserted-by":"publisher","DOI":"10.1016\/j.amc.2009.03.090"},{"key":"jncr.2010040104-10","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2007.05.007"},{"key":"jncr.2010040104-11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfranklin.2008.11.003"},{"key":"jncr.2010040104-12","doi-asserted-by":"crossref","unstructured":"Mishra, S. K. (2007). Performance of Differential Evolution and Particle Swarm Methods on Some Relatively Harder Multi-modal Benchmark Functions. Unpublished Munich personal RePec (No. 1743).","DOI":"10.2139\/ssrn.937147"},{"key":"jncr.2010040104-13","doi-asserted-by":"crossref","unstructured":"Modegi, T. (2008). Small object recognition techniques based on structured template matching for high-resolution satellite images. SICE Annual Conference, 2168-2173.","DOI":"10.1109\/SICE.2008.4655022"},{"issue":"5","key":"jncr.2010040104-14","first-page":"17","article-title":"An investigation of significant object recognition techniques.","volume":"9","author":"V. N.Pawar","year":"2009","journal-title":"International Journal of Computer Science and Network Security"},{"key":"jncr.2010040104-15","first-page":"11","article-title":"Particle swarm optimization for object recognition in computer vision (","volume":"5027","author":"H. A.Perlin","year":"2008","journal-title":"LNCS"},{"key":"jncr.2010040104-16","unstructured":"Perlin, H. A., Lopes, H. S., & Centeno, T. M. (2008). Object Recognition in Digital Images Using Particle Swarm Optimization. Unpublished master\u2019s thesis, Federal University of Technology Paran\u00e1, Brazil."},{"key":"jncr.2010040104-17","doi-asserted-by":"crossref","unstructured":"Pham, D. T., Ghanbarzadeh, A., Ko\u00e7, E., Otri, S., Rahim, S., & Zaidi, M. (2006). The bees algorithm \u2013 a novel tool for complex optimisation problems. In Proceedings of the International Conference on Intelligent Production Machines and Systems (pp. 453-459).","DOI":"10.1016\/B978-008045157-2\/50081-X"},{"key":"jncr.2010040104-18","unstructured":"Pham, D. T., Ghanbarzadeh, A., Ko\u00e7, E., Otri, S., Rahim, S., & Zaidi, M. (2008). Generating branded product concepts: comparing the bees algorithm and an evolutionary algorithm. In Proceedings of the 4th International Conference on Intelligent Production Machines and Systems (pp. 398-403)."},{"key":"jncr.2010040104-19","doi-asserted-by":"crossref","unstructured":"Pham, D. T., Soroka, A. J., Ghanbarzadeh, A., & Koc, E. (2006). Optimising neural networks for identification of wood defects using the bees algorithm. In Proceedings of the International Conference on Industrial Informatics (pp. 1346-1351).","DOI":"10.1109\/INDIN.2006.275855"},{"issue":"1","key":"jncr.2010040104-20","first-page":"91","article-title":"Template matching in digital images using a compact genetic algorithm with elitism and mutation. Journal of Circuits","volume":"19","author":"R. R.Silva","year":"2010","journal-title":"Systems and Computers"},{"key":"jncr.2010040104-21","first-page":"1109","article-title":"A compact genetic algorithm with elitisim and mutation applied to image recognition (","volume":"5227","author":"R. R.Silva","year":"2008","journal-title":"LNCS"},{"key":"jncr.2010040104-22","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2008.09.001"},{"key":"jncr.2010040104-23","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1109\/ICIP.1995.537549","article-title":"Genetic algorithms for object recognition in a complex scene. In","volume":"2","author":"D. L.Swets","year":"1995","journal-title":"Proceedings of the International Conference on Image Processing"},{"issue":"3","key":"jncr.2010040104-24","first-page":"1","article-title":"Collective decision-making in honey bee foraging dynamics.","volume":"9","author":"V.Tereshko","year":"2005","journal-title":"Computing and Information Systems"},{"key":"jncr.2010040104-25","doi-asserted-by":"crossref","unstructured":"Zhao, X., Lee, M. E., & Kim, S. H. (2008). Improved Image Thresholding using Ant Colony Optimization Algorithm. In Proceedings of the International Conference on Advanced Language Processing and Web Information Technology (pp. 201-215).","DOI":"10.1109\/ALPIT.2008.105"}],"container-title":["International Journal of Natural Computing Research"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=45886","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T17:06:57Z","timestamp":1654103217000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/jncr.2010040104"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2010,4,1]]},"references-count":26,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2010,4]]}},"URL":"https:\/\/doi.org\/10.4018\/jncr.2010040104","relation":{},"ISSN":["1947-928X","1947-9298"],"issn-type":[{"value":"1947-928X","type":"print"},{"value":"1947-9298","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,4,1]]}}}