Now a days researchers are using natural images for their research work. Natural images contain text also. Text in natural images typically adds meaning to an object or scene. So extract the text from natural images is very important for applications which are processing with text. However, variations of text due to differences in size, style, orientation, and alignment, as well as low image contrast and complex background make the problem of automatic text extraction extremely challenging. Extracting text from an image can be done with image processing which deals with digital images. Extraction of text involves in different stages. They are named as preprocessing, detection, localization, extraction and recognition of the text from a given image. The aim of pre-processing is an improvement of the image data that suppresses unwanted distortions or enhances some image features important for further processing. So pre-processing is important stage to improve the image quality. This paper presents the existing histogram techniques for preprocessing and proposed a new technique named enhanced CLAHE which gives best contrast enhancement for natural scene images with text.

preprocessing, noise removal, image enhancement, histogram techniques, skew correction

[1] Asit kumar et al., “Detection and Recognition of Text from Image using Contrast and Edge Enhanced MSER Segmentation and OCR”, IJO-Science,ISSN: 2455-0108.
[2]Balvant Singh, Ravi Shankar Mistra, Puran Gour, “Analysis of Contrast Enhancement Techniques For Underwater Image,” IJCTEE Volume 1, Issue 2, 2009
[3] Gllavata et al., “A Robust algorithm for Text Detection in Images” , 2017.
[4] Huang et al., “A SWT Verified Method of Natural Scene Text Detection”, Advances in Computational Intelligence ISBN : 978-1-61804-343-6
[5] A.J.Jadhav, Vaibhav Kolhe, Sagar peswe, “Text Extraction from Images : A Survey”, International Journal of Advanced Research in Computer Science and Software Engineering, volume 3,Issue 3, March 2013.
[6] Neumann et al., “Realtime Scene Text Localization and Recognition”, IEEE journal ,2012.
[7] Partha sarathi giri “Text Information Extraction And Analysis From Images Using Digital Image Processing Tchniques” , Special Issue of International Journal on Advanced Computer Theory and Engineering (IJACTE) , ISSN : 2319 -2526, Volume 2, Issue 1,2013
[8] Raimondo Schettini and Silvia Corchs, “Review Article - Underwater Image Processing : State of the Art of restoration and Image Enhancement Methods,” EURASIP Journal on Advances in Signal Processing, Volume 2010.
[9] Rajesh Garg, Bhawna Mittal, sheetal garg, “Histogram Equalization Techniques For Image Enhancement,” International Journal of Electronics & Communication Technology, Volume 2, Issue 1, March 2011.
[10] Rajesh Kumar Rai, Puran Gour, Balvant Singh, “Underwater Image Segmentation using CLAHE Enhancement and Thresholding,” International Journal of Emerging Technology and Advanced Engineering, ISSN 2250-2459, Volume 2, Issue 1, January 2012
[11] Ramyashree N, Pathra P, Shruthi T V, Dr. JharnaMajumdar, “Enhacement of Aerial and Medical Image using Multi resolution pyramid,” Special Issue of IJCCT Vol. 1 Issue 2,3,4; International Conferecnce - ACCTA-2010
[12] Ramesh Neelamani, Thesis report on “ Inverse problems in image processing ” Electrical and Computer Engineering Rice University, Houston, Texas.
[13] Reginald L. Lagendijk and Jan Biemond, “Basic methods for image restoration and Identification ”, Lagendijk – Biemond , February, 1999.
[14] Seokjun et al., “Text Region Extraction in High Contrasting Image”, International Journal of Future Computer and Communication, Vol.6, No. 3, September 2017.
[15] Stephen M. Pizer, E. Philip Amburn, John D. Austin, Robert Cromartie, “Adaptive Histogram Equalization and Its Variations,” Computer Vision, Graphics, And Image Processing 39, 355-368 (1987) .
[16] Yin et al., “Robust Text Detection in Natural Scene images”, IEEE journal , June 2013.
[17] K. Zuiderveld, “Contrast Limited Adaptive Histogram Equalization”, Academic Press Inc.,