{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,20]],"date-time":"2024-07-20T07:47:07Z","timestamp":1721461627199},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,5,29]],"date-time":"2020-05-29T00:00:00Z","timestamp":1590710400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,5,29]],"date-time":"2020-05-29T00:00:00Z","timestamp":1590710400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["EURASIP J. Adv. Signal Process."],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In this paper, a vision-based patient identification recognition system based on image content analysis and support vector machine is proposed for medical information system, especially in dermatology. This proposed system is composed of three parts: pre-processing, candidate region detection, and digit recognition. To consider the efficiency of the proposed scheme, image normalization is performed. The color information is used to identify camera-captured screen images. In the pre-processing part, the effect of noise in captured screen images is reduced by a bilateral filter. The color and spatial information is used to initially and roughly locate the candidate region. To reduce the skew effect, a skew correction algorithm based on the Hough transform is developed. A template matching algorithm is used to find special symbols for locating the region of interest (ROI). For digit segmentation, digits are segmented in the ROI based on the vertical projection and adaptive thresholding. For the digit recognition, some features are measured from each digit segment and a classifier based on the support vector machine is applied to recognize digits.<\/jats:p><jats:p>The experiment\u2019s results show that the proposed system could effectively not only use color information to distinguish the captured screen images from the skin images but also detect the ROIs. After the digit segmentation, the accuracy rates of digit recognition are 98.4% and 94.2% for the proposed system and the Tesseract Optical Character Recognition (OCR) software, respectively. These results demonstrate that the proposed system outperforms the Tesseract OCR software in terms of the accuracy rate of digit recognition.<\/jats:p>","DOI":"10.1186\/s13634-020-00686-3","type":"journal-article","created":{"date-parts":[[2020,5,29]],"date-time":"2020-05-29T09:02:43Z","timestamp":1590742963000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Vision-based patient identification recognition based on image content analysis and support vector machine for medical information system"],"prefix":"10.1186","volume":"2020","author":[{"given":"Guo-Shiang","family":"Lin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sin-Kuo","family":"Chai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hsiang-Min","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jen-Yung","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,5,29]]},"reference":[{"issue":"03","key":"686_CR1","doi-asserted-by":"crossref","first-page":"1450007","DOI":"10.1142\/S0218001414500074","volume":"28","author":"GUO-SHIANG LIN","year":"2014","unstructured":"G.-S. Lin, S.-K. Chai, W.-C. Yeh, and Y.-C. Lin, \u201cSuspicious region detection and identification based on intra-\/inter-frame analyses and fuzzy classifier for breast magnetic resonance imaging,\u201d International Journal of Pattern Recognition and Artificial Intelligence, Vol. 28, No. 3, pp. 1450007-1- 1450007-26, May 2014.","journal-title":"International Journal of Pattern Recognition and Artificial Intelligence"},{"issue":"23","key":"686_CR2","doi-asserted-by":"crossref","first-page":"25369","DOI":"10.1007\/s11042-017-4504-5","volume":"76","author":"G-S Lin","year":"2017","unstructured":"G.-S. Lin, N.-M. Tuan, W.-J. Chen, Detecting region of interest for cadastral images in Taiwan. Multimed. Tools Appl.76(23), 25369\u201325389 (2017)","journal-title":"Multimed. Tools Appl."},{"issue":"2","key":"686_CR3","first-page":"204","volume":"6","author":"MA Mohamad","year":"2015","unstructured":"M.A. Mohamad, H. Hassan, D. Nasien, H. Haron, A review on feature extraction and feature selection for handwritten character recognition. Int. J. Adv. Comput. Sci. Appl.6(2), 204\u2013212 (2015)","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"686_CR4","unstructured":"S. Maji and J. Malik, \u201cFast and accurate digit classification,\u201d Technical Report No. UCB\/EECS-2009-159, November 25, 2009."},{"key":"686_CR5","unstructured":"E. Tuba, M. Tuba, and D. Simian, \u201cHandwritten digit recognition by support vector machine optimized by bat algorithm,\u201d 24th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG 2016), pp. 367\u2013376, 2016."},{"key":"686_CR6","unstructured":"M. Sonka, V. Hlavac, and R. Boyle, Image processing, analysis, and machine vision, Thomson, 2008."},{"key":"686_CR7","unstructured":"C. Tomasi, and R. Manduchi, \u201cBilateral filtering for gray and color images,\u201d Computer Vision, pp.839-746, Jan. 1998."},{"key":"686_CR8","doi-asserted-by":"crossref","unstructured":"G.-S. Lin, C.-Y. Chen, C.-T. Kuo, and W.-N. Lie, \u201cA computing framework of adaptive support-window multi-lateral filter for image and depth processing.\u201d IEEE Trans. Broadcast., Vol. 60, pp. 452-463, June 2014.","DOI":"10.1109\/TBC.2014.2330391"},{"key":"686_CR9","doi-asserted-by":"crossref","unstructured":"Z. Liu, W. Chen, Y. Zou, and C. Hu, \u201cRegions of interest extraction based on HSV color space\u201d, Industrial Informatics (INDIN), pp. 481\u2013485, July 2012.","DOI":"10.1109\/INDIN.2012.6301214"},{"key":"686_CR10","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1016\/j.patcog.2005.10.030","volume":"40","author":"CH Chou","year":"2007","unstructured":"C.H. Chou, S.Y. Chu, F. Chang, Estimation of skew angles for scanned documents based on piecewise covering by parallelograms. Pattern Recogn.40, 443\u2013455 (2007)","journal-title":"Pattern Recogn."},{"key":"686_CR11","unstructured":"S. B. Rezaei, A. Sarrafzadeh, and J. Shanbehzadeh, \u201cSkew detection of scanned document images,\u201d Proceedings of the International MultiConference of Engineers and Computer Scientists, 2013."},{"key":"686_CR12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.13176\/11.635","volume":"1","author":"A Alaei","year":"2016","unstructured":"A. Alaei, P. Nagabhushan, U. Pal, F. Kimura, An efficient skew estimation technique for scanned documents: an application of piece-wise painting algorithm. Journal of Pattern Recognition Research1, 1\u201314 (2016)","journal-title":"Journal of Pattern Recognition Research"},{"key":"686_CR13","unstructured":"G. Bradski, and A. Kaehler, Learning OpenCV: computer vision with the OpenCV library, O'Reilly Media, Sebastopol, CA, Sep. 2008."},{"key":"686_CR14","unstructured":"Atam P. Dhawan, Medical Image Analysis, John Wiley & Sons, Inc, 2003."},{"key":"686_CR15","first-page":"130","volume":"7","author":"CW Su","year":"2005","unstructured":"C.W. Su, H.Y. Liao, H.R. Tyan, K.C. Fan, L.H. Chen, A motion-tolerant dissolve detection algorithm. IEEE Trans. Multimedia7, 130\u2013140 (2005)","journal-title":"IEEE Trans. Multimedia"},{"key":"686_CR16","doi-asserted-by":"crossref","first-page":"1281","DOI":"10.1109\/76.974682","volume":"11","author":"CL Huang","year":"2001","unstructured":"C.L. Huang, B.Y. Liao, A robust scene-change detection method for video segmentation. IEEE Trans. Circuits and Systems for Video Technology11, 1281\u20131288 (2001)","journal-title":"IEEE Trans. Circuits and Systems for Video Technology"},{"key":"686_CR17","unstructured":"G. Deng and L. W. Cahill, \u201cAn adaptive Gaussian filter for noise reduction and edge detection,\u201d 1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference, pp. 1615 \u2013 1619, Nov. 1993."},{"issue":"16","key":"686_CR18","doi-asserted-by":"crossref","first-page":"9775","DOI":"10.1007\/s11042-015-2797-9","volume":"75","author":"G-S Lin","year":"2016","unstructured":"G.-S. Lin, M.-K. Chang, Y.-J. Chang, C.-H. Yeh, A gender classification scheme based on multi-region feature extraction and information fusion for unconstrained images. Multimed. Tools Appl.75(16), 9775\u20139795 (2016)","journal-title":"Multimed. Tools Appl."},{"issue":"3","key":"686_CR19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1961189.1961199","volume":"2","author":"CC Chang","year":"2011","unstructured":"C.C. Chang, C.J. Lin, LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol.2(3), 1\u201327 (2011)","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"686_CR20","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1142\/S0218001409007521","volume":"23","author":"GS Lin","year":"2009","unstructured":"G.S. Lin, M.K. Chang, S.T. Chiu, A feature-based scheme for detecting and classifying video-shot transitions based on spatio-temporal analysis and fuzzy classification. Int. J. Pattern Recognit. Artif. Intell.23, 1179\u20131200 (2009)","journal-title":"Int. J. Pattern Recognit. Artif. Intell."}],"container-title":["EURASIP Journal on Advances in Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13634-020-00686-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13634-020-00686-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13634-020-00686-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,28]],"date-time":"2021-05-28T23:38:10Z","timestamp":1622245090000},"score":1,"resource":{"primary":{"URL":"https:\/\/asp-eurasipjournals.springeropen.com\/articles\/10.1186\/s13634-020-00686-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,29]]},"references-count":20,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["686"],"URL":"https:\/\/doi.org\/10.1186\/s13634-020-00686-3","relation":{},"ISSN":["1687-6180"],"issn-type":[{"value":"1687-6180","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,29]]},"assertion":[{"value":"23 August 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 May 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 May 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This study does not involve human participants, human data, or human tissue.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"In the manuscript, there is no any individual person\u2019s data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"27"}}