{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T09:06:26Z","timestamp":1723194386403},"reference-count":3,"publisher":"World Scientific Pub Co Pte Lt","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[1997,2]]},"abstract":" This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solution used to solve them. <\/jats:p> The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. <\/jats:p> The system has been designed using a modular approach. Sub-modules can be upgraded and\/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. <\/jats:p> The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. <\/jats:p> The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80% <\/jats:p>","DOI":"10.1142\/s0129065797000148","type":"journal-article","created":{"date-parts":[[2003,10,13]],"date-time":"2003-10-13T05:47:33Z","timestamp":1066024053000},"page":"113-126","source":"Crossref","is-referenced-by-count":101,"title":["A Neural Network Based Artificial Vision System for Licence Plate Recognition"],"prefix":"10.1142","volume":"08","author":[{"given":"Sorin","family":"Draghici","sequence":"first","affiliation":[{"name":"Vision and Neural Networks Laboratory, Dept. of Computer Science, Wayne State University, 431 State Hall, Detroit, 48202 MI, USA"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"p_6","first-page":"555","author":"Draghici S.","year":"1994","journal-title":"Proc. World Congr. Neural Networks (San Diego)"},{"key":"p_9","first-page":"289","author":"Kittler J.","year":"1984","journal-title":"Int. Conf. Pattern Recogn. (Montreal)"},{"key":"p_13","volume":"23","author":"Weska J. S.","year":"1974","journal-title":"IEEE Trans. Comput."}],"container-title":["International Journal of Neural Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0129065797000148","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T21:49:46Z","timestamp":1565128186000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0129065797000148"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1997,2]]},"references-count":3,"journal-issue":{"issue":"01","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1997,2]]}},"alternative-id":["10.1142\/S0129065797000148"],"URL":"http:\/\/dx.doi.org\/10.1142\/s0129065797000148","relation":{},"ISSN":["0129-0657","1793-6462"],"issn-type":[{"value":"0129-0657","type":"print"},{"value":"1793-6462","type":"electronic"}],"subject":[],"published":{"date-parts":[[1997,2]]}}}
