Open Access Open Access  Restricted Access Subscription Access

Different Image Processing Techniques to Detect Text from Natural Images: A Survey

Priyanka Muchhadiya, Poorvi H. Patel

Abstract


Texture analysis can provide very useful and vital information for content-based image analysis. Text recognition and analysis includes many applications such as: license plate recognition, sign detection as well translation, helping tourists and blind persons to understanding environment, drawing attention of a driver, content-based image search and so on. Locating text in case of variation in style, colour, as well as complex image background makes text reading from images more challenging. In this paper, the various techniques available for detecting and recognizing text are explained. Finally, a hybrid approach using segmentation is explained which can improve the qualitative texture analysis among other techniques.

Keywords: Text detection, text localization, text recognition


Full Text:

PDF

References


Pan YF, Hou X, Liu CN. ”A Hybrid Approach to Detect and Localize Texts in Natural Scene Images.” IEEE Trans on Image Processing. 2011; 20(3) .

Liu YX, Goto S, Ikenaga T. “A contour-based robust algorithm for text detection in color images.” IEICE Trans. Inf. Syst. 2006; E89-D(3): 1221–30p.

Chen XL, Yang J, Zhang J, Waibel A. “Automatic detection and recognition of signs from natural scenes.” IEEE Trans. Image Process. 2004; 13(1): 87–99p.

M. Cai, J. Song, and M. R. Lyu, “A new approach for video text detection,” in Proc. Int. Conf. Image Process.,Rochester, NY, Sep. 2002, 117–120p.

Boykov Y, Veksler O, Zabih R. Fast approximate energy minimization via graph cuts. IEEE Trans. Pattern Anal.Mach. Intell. 2001; 23(11):1222–39p.

Liang J, Doermann D, Li H. “Camera-based analysis of text and documents: A survey.” Int. J. Document Anal. Recogn. 2005; 7: 84–104p.

Wu V, Manmatha R, Riseman EM. “Text Finder: An Automatic System to Detect and Recognize Text in Images.” IEEE Transactions on Pattern Analysis and Machine Intelligence. 2009; 21: 1224-9p.

Yi C, Tian Y. “Text string detection from natural scenes by structure-based partition and grouping.” IJFST. 2011; 19(12).

Elie Bursztein, Matthieu artin, Stanford University, Text-based CAPTCHA Strengths and WeaknessesACM(CSS 2011).

Pranob, K Charles, V. Harish, “A Review on the Various Techniques used for Optical Character Recognition” IJJST Vol. 2, Issue 1,Jan-Feb 2012. Miss.Poonam B.Kadam, Mrs. Latika R. Desai “A Hybrid Approach to Detect and Recognize Texts in Images” IJRCCT 2013; 2(7).


Refbacks

  • There are currently no refbacks.