@inproceedings{scholars1766,
           pages = {306--310},
         journal = {Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011},
           title = {OCR signage recognition with skew \& slant correction for visually impaired people},
         address = {Malacca},
            year = {2011},
             doi = {10.1109/HIS.2011.6122123},
            note = {cited By 11; Conference of 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011 ; Conference Date: 5 December 2011 Through 8 December 2011; Conference Code:88378},
            isbn = {9781457721502},
          author = {Hairuman, I. F. Bt. and Foong, O.-M.},
        abstract = {It is a challenge for visually impaired people (VIPs) to navigate independently whenever they attempt to find their way in unfamiliar buildings searching for amenities (i.e. exits, ladies/gents toilets) even with a walking stick or a guide dog. Camera-based computer vision systems have the potential to assist VIPs in independent navigation or way finding in unfamiliar places. To leverage on previous research of Signage Recognition Framework which could only recognize public signage with slanted angle less than30{\^A}o, an improved OCR signage recognition model with skew and slant correction in public signage is presented. The proposed OCR method consists of Canny edge detection algorithm, Hough Transformation and Shearing Transformation were used to detect and correct skewed and slanted images. The proposed model would capture a public signage image, compare the image in the database using template matching algorithm and convert to machine readable text in a text file. The text will then be processed by Microsoft Speech Application Program Interface (SAPI) speech synthesizer and translated to voice as output. Experiments were conducted on 5 blind folded subjects to test the performance of the model. The proposed OCR recognition model has achieved satisfactory recognition rate of 82.7. {\^A}{\copyright} 2011 IEEE.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84856723727&doi=10.1109\%2fHIS.2011.6122123&partnerID=40&md5=5c7199da3b192d8c7f254a61980a192e},
        keywords = {Canny edge detection; Computer vision system; Hough Transformation; MicroSoft; Recognition models; Recognition rates; slant correction; Speech applications; Speech synthesizer; Template-matching algorithms; Text file; Visually impaired; Visually impaired people; Way finding, Edge detection; Ferry boats; Intelligent systems; Optical character recognition; Shearing; Template matching, Algorithms}
}