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http://dx.doi.org/10.7848/ksgpc.2019.37.4.219

Recognition of Flat Type Signboard using Deep Learning  

Kwon, Sang Il (Department of Spatial Information Engineering, Namseoul University)
Kim, Eui Myoung (Department of Spatial Information Engineering, Namseoul University)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.37, no.4, 2019 , pp. 219-231 More about this Journal
Abstract
The specifications of signboards are set for each type of signboards, but the shape and size of the signboard actually installed are not uniform. In addition, because the colors of the signboard are not defined, so various colors are applied to the signboard. Methods for recognizing signboards can be thought of as similar methods of recognizing road signs and license plates, but due to the nature of the signboards, there are limitations in that the signboards can not be recognized in a way similar to road signs and license plates. In this study, we proposed a methodology for recognizing plate-type signboards, which are the main targets of illegal and old signboards, and automatically extracting areas of signboards, using the deep learning-based Faster R-CNN algorithm. The process of recognizing flat type signboards through signboard images captured by using smartphone cameras is divided into two sequences. First, the type of signboard was recognized using deep learning to recognize flat type signboards in various types of signboard images, and the result showed an accuracy of about 71%. Next, when the boundary recognition algorithm for the signboards was applied to recognize the boundary area of the flat type signboard, the boundary of flat type signboard was recognized with an accuracy of 85%.
Keywords
Signboard Detection; Flat Type; Faster Region-Based Convolutional Neural Network; Watershed; K-Means Clustering; Boundary Area;
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1 Ahn, H.Y. and Lee, J.T. (2018), Classification of vehicles based on faster R-CNN suitable for use in actual road environments, Journal of Korean Institute of Intelligent Systems, Vol. 28, No. 3, pp. 210-218. (in Korean with English abstract)   DOI
2 Cha, S.H. and Kim, J.H. (2017), Analysis on managemental characteristics and problems of outdoor advertisement in Seoul metropolitan city, The Korean Society Of Design Culture, Vol. 23, No. 4, pp. 767-779. (in Korean with English abstract)
3 Choi, H.S. and Kim, E.M. (2015), Detection of road signs region and recognition of directional information, Proceedings of Korean Society for Geospatial Information Science, September 2015, Korea, pp. 197-198.
4 Claudio, R.J. and Rodrigo, S. (2004), Rectangle detection based on a windowed hough transform, Proceedings of the XVII Brasilian Symposium on Computer Graphics and Image Processing, October 2004, Brazil, pp. 113-120.
5 Hua, S. and Xiaoou, T. (2003), Generic sign board detection in images, MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval, 7 July 2003, California, USA, pp. 144-149.
6 Jang, J.W. and Park, G.M. (2017), License plate recognition system based on normal CCTV, Journal of the Institute of Electronics and Information Engineers, Vol. 54, No. 8, pp. 89-96. (in Korean with English abstract)   DOI
7 Kim, B.J., Kim, D.H., and Lee, J.H. (2016), An improved license plate recognition technique in outdoor image, Journal of Korean institute of intelligent systems, Vol. 26, No. 5, pp. 423-431. (in Korean with English abstract)   DOI
8 Ministry of the Interior and Safety(MOIS), (2016), Outdoor Advertising Policy Focus, ISSN 2288-2456, Korea out of home advertising center, Seoul, pp. 1-112.
9 Kwon, S.I. and Kim, E.M. (2019), Recognition of signboard type using faster R-CNN, 2019 KAGIS Spring Conference and Inter-Korean Exchanges and GIS Symposium, 16 May 2019, Chuncheon, Korea, pp. 109-110.
10 Kwon, S.I. and Kim, E.M. (2019), Recognition of horizontalflat type signboard using Images, 2019 Spring Conference, 31 May 2019, Busan, Korea, pp. 267-268.
11 Lee, M.S. and Choi, G.S. (2018), Comparative analysis on characteristics of color uses for signboard between before and after signboard improvement project - focused on signboard improvement project in Ganghwa-gun, Incheon, Journal of Korea Society of Color Studies, Vol. 32, No. 2, pp. 51-63. (in Korean with English abstract)   DOI
12 Lim, H.C., Kaushik, D., and Jo, K.H. (2009), Geometrical reorientation of distorted road sign using projection transformation for road sign recognition, Journal of Institute of Control, Robotics and Systems, Vol. 15, No. 11, pp. 1088-1095. (in Korean with English abstract)   DOI
13 Tao, Z., Jie, Z., and Wenjing, J. (2018), Fast and robust road sign detection in driver assistance systems, Applied Intelligence, Vol. 48, No. 11, pp. 4113-4127.   DOI
14 Ministry of the Interior and Safety(MOIS), (2018), 2018 Outdoor Advertising Statistics, ISSN 2635-5086, Korea out of home advertising center, Seoul, pp. 1-196.