Email this article 
Open Access
Subscription or Fee Access
Review on Effective Technique for Detection and Recognition of Text from Road Traffic Panels
Abstract
In intelligent transportation systems (ITS), traffic panel detection and recognition is quite difficult, due to its number of variation in panel types and the huge variation in the information depicted in traffic panels. This paper presents an approach for detecting the presence or absence of traffic panels on natural highway images and to recognize the information contained on street traffic panels. The proposed system detects street traffic panels using appropriate algorithm as well as by using Edge Profile Base Detection (EPBD) method for the text detection from accurate traffic panel. The text detection stage detects the presence of text from the given street image. According to the features utilized, text recognition methods can be dividing into two types: region-based and texture-based. Challenging part of street text detection systems as well as Devanagari text conversions is that, sometimes-street images containing varying in text due to the shape, size, font, alignment, orientation, complex background & foreground. The main goal of this paper is to present the review of different methods presented for text detection, recognition, conversion as well as for extraction on images.
Keywords
References
P. H. Rathod, M. L. Dhore, R. M. Dhore,”Hindi & Marathi To english transliteration using SVM,”International journal on natural language computing(IJNLC),Vol.2,No.4,pp.1-17,2013.
N. Senthil kumaran and R. Rajesh,” Edge Detection Techniques for Image Segmentation – A Survey of Soft Computing Approaches,” International Journal of Recent Trends in Engineering, Vol. 1, No. 2, pp.250-254, May 2009.
Gonzalez, L.M. Bergasa, J. Javier Yebes, M.A. Sotelo,” Automatic Information Recognition of Traffic Panels using SIFT descriptors and HMMs,” International IEEE Annual Conference on Intelligent Transportation Systems, pp. 1289-1294, September 2010.
Mahesh Jangid, “Devanagari Isolated Character Recognition by Using Statistical Features,” International Journal of Computer Science and Engg. Vol. 3, No.2, pp. 2400 –2407, 6, June 2011.
Peter Peer, Andrej Ikica,” An improved edge profile based method for text detection in images of natural scenes,” International Conference on Computer as a Tool (EUROCON), pp.1-4, 2011.
C.P. Sumathi, T. Santhanam, N. Priya,” Techniques and challenges of automatic text extraction in complex image: a survey,” Journal of Theoretical and Applied Information Technology,Vol. 35 No.2, pp. 225-235,2012.
Sankaran, C. V. Jawahar and Naven,"Recogniton of printed Devanagari text using BLSTM Neural Network," Patern Recogniton (ICPR), 2012 21st International Conference on.IEEE, 2012.
Dr. G. S. Sable, Prof. Sheetal A. Nirve,” Optical character recognition for printed text in Devanagari using ANFIS,” International Journal of Scientific & Engineering Research, Vol. 4, No. 10, October-2013, PP.236-241.
S. Dixit, Dhore, M. and R. Dhore, “Hindi and Marathi to English NE Transliteration Tool using Phonology and Stress Analysis,” Proceedings of coling Demonstration Papers, pp. 111-118, 2012.
Ashoka H.N., Manjaiah D.H., Rabindranath Bera,” Feature Extraction Technique for Neural Network Based Pattern Recognition,” International Journal on Computer Science and Engineering (IJCSE), Vol. 4 No. 03, pp. 331-339, March 2012.
Jonathan Fabrizio, Beatriz Marcotegui and Matthieu Cord,” Text detection in street level images,” pattern anal, springer Verlag, pp. 519-533, 2013.
Gonzalez, L.M. Bergasa, J. Javier Yebes and J. Almazan,” Traffic Panels Detection Using Visual Appearance,” Intelligent Vehicles Symposium (IV), pp. 1221 – 1226, June 2013.
Shruti Agarwal, Dr. Naveen Hemarjani,” Offline Handwritten Character Recognition with Devanagari Script,” IOSR Journal of Computer Engineering (IOSR-JCE), Vol.12No.6, pp.82-86(May. - Jun. 2013.
Sanket Rege, Rajendra Memane, Mihir Phatak, Parag Agarwal,” 2D GEOMETRIC SHAPE AND COLOR RECOGNITION USING DIGITAL IMAGE PROCESSING, “International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering ,Vol. 2, No.6, pp. 2479-2487, June 2013.
Rajesh K. Bawa1 and Ganesh K. Sethi,”A binarization technique extraction for Devanagari text from camera based images,” International Journal of Signal & Image Processing (SIPIJ) Vol.5, No.2, April 2014.
Ajay Garg, Simpel Jindal “To Extract Feature of Handwritten Devnagari Script,” International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, No. 7, pp. 7501-7503, July 2014.
Ms. Saumya sucharita Sahoo and Prof. Smita Tikar,” Review methods of scene text detection and its challenges,” International Journal of electronics and communication Engineering (IJECET), Vol.5 No.01, pp. 74-81, January 2014.
Poonam M.Ingle, P. P. Gumaste,” Handwritten Devanagari script recognition using phase correlation,” Proceedings of IRF International Conference, pp. 96-99, 30th March-2014.
Samabia Tehsin, Asif Masood, Sumaira Kausar, and Fahim Arif,” Fuzzy-Based Segmentation for Variable Font-Sized Text Extraction from Images/Videos,” Hindawi Publishing Corporation Mathematical Problems in Engineering, pp. 1-10, 2014.
Parminder Singh, Kamaljeet Kaur,” Review of machine transliteration systems,” International Journal of Advanced Engineering Applications, Vol. 7, No.3, pp.72-80, 2014.
Alvaro Gonzalez,” Text Detection and Recognition on Traffic Panels from Street-Level Imagery Using Visual Appearance,” IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, pp.1-11, 2014.
Sandeep Sharma and Jai Prakash,” A Survey of Image to Text Detection Methodology,” Department of Computer Science & Engineering”, pp. 1-4, 2011.
Miguel Angel Garcia-Garrido,”Automatic Traffic Signs and Panels Inspection System Using Computer Vision,” IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, Vol. 12, No. 2, pp. 485-499, JUNE 2011.
Sukhpreet Singh,” Optical Character Recognition Techniques A survey,” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), Vol.2, No. 6, June 2013.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.