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About this, neural network-based approaches are very popular in visual inspection because of their high accuracy and efficiency of aligning images. However, such methods are difficult to identify the structure and parameters of neural network. In this study, a Takagi-Sugeno-Kang-type neuro-fuzzy network (NFN) with data-mining-based evolutionary learning algorithm (DMELA) is proposed. Compared with traditional learning algorithms, DMELA combines the self-organization algorithm (SOA), data-mining selection method (DMSM), and regularized least square (RLS) method to not only determine a suitable number of fuzzy rules, but also automatically tune the parameters of NFN. Experimental results are shown to demonstrate superior performance of the DMELA constructed image alignment system over other typical learning algorithms and existing alignment systems. Such system is useful to develop accurate and efficient image alignment systems.<\/jats:p>","DOI":"10.1186\/1687-6180-2011-96","type":"journal-article","created":{"date-parts":[[2011,11,8]],"date-time":"2011-11-08T07:27:16Z","timestamp":1320737236000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Efficient and accurate image alignment using TSK-type neuro-fuzzy network with data-mining-based evolutionary learning algorithm"],"prefix":"10.1186","volume":"2011","author":[{"given":"Chi-Yao","family":"Hsu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi-Chang","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheng-Fuu","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2011,11,7]]},"reference":[{"key":"93_CR1","first-page":"1507","volume-title":"Proceedings of IEEE International Conference on System, Man and Cybernetics","author":"I Elhanany","year":"2000","unstructured":"Elhanany I, Sheinfeld M, Beckl A, Kadmon Y, Tal N, Tirosh D: Robust image registration based on feedforward neural networks. 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