Open AccessText Extraction from Hoardings by Hybrid Model
Author(s) -
D. Jayaram,
J. Shiva Sai,
C. Harishwar Reddy,
V. Kamakshi Prasad
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.d6650.049420
Subject(s) - artificial intelligence , computer science , pattern recognition (psychology) , orientation (vector space) , symmetry (geometry) , pixel , computer vision , image (mathematics) , mathematics , geometry
There are various techniques available to detect and extract the text from hoardings. Still it is a challenging task to detect text from images of various sizes, orientation, illuminations and color. With a view to improve on these, a hybrid method of text extraction and detection is proposed. The proposed method uses a symmetry features like Mutual Magnitude Symmetry (MMS), Mutual Direction Symmetry (MDS) and Gradient Vector Symmetry (GVS) to identify text pixel candidates from natural scenes. The proposed method is tested on different datasets like ICDAR, CUTE 80 and also images from mobile phones. Implementation of MMS, MDS, and GVS methods on above datasets has been carried out. Text extraction from hoardings in ICDAR is giving 74% accuracy, CUTE80 is giving 76% and on mobile images 83% of accuracy is achieved.