05-09-2016, 12:21 PM
1452822317-documentationppt.pptx (Size: 78.6 KB / Downloads: 4)
ABSTRACT
Segmentation of text from badly degraded document images is very challenging tasks due to the high inter/intra variation between the document background and the foreground text of different document images. In this paper, we propose a novel document image binarization technique that addresses these issues by using adaptive image contrast. The Adaptive Image Contrast is a combination of the local image contrast and the local image gradient that is tolerant to text and background variation caused by different types of document degradations. The proposed method is simple, robust, and involves minimum parameter tuning.
EXISTING SYSTEM
The early window-based adaptive thresholding techniques proposed in “Adaptive document image binarization,” estimate the local threshold by using the mean and the standard variation of image pixels within a local neighborhood window.
The local contrast method proposed in Bernsen’s “Dynamic thresholding of gray-level images,” is simple and depends upon the maximum and minimum intensities within a local neighborhood windows of an image pixel (i,j) respectively.
EXISTING SYSTEM DRAWBACKS
The main drawback of these window-based thresholding techniques is that the thresholding performance depends heavily on the window size and hence the character stroke width.
The method used is simple, but cannot work properly on degraded document images with a complex document background.
PROPOSED SYSTEM
This paper is on the development of new approaches for restoration of degraded document images.
In the proposed document image binarization techniques, an adaptive contrast map is first constructed for a given degraded document image and the text stroke edges are then detected through the combination of the binarized adaptive contrast map and the canny edge map.
The text is then segmented based on the local threshold that is estimated from the detected text stroke edge pixels.
Some post-processing is further applied to improve the document binarization quality.
FUTURE ENHANCEMENT
The proposed adaptive image contrast based document image binarization technique that is tolerant to different types of document degradation such as uneven illumination and document smear. Further improvement of this paper is, we measure the image quality performance.
SOFTWARE REQUIREMENTS
MATLAB 7.14 Version R2012
The MATLAB high-performance language for technical computing integrates computation, visualization, and programming.
Data Exploration ,Acquisition ,Analyzing &Visualization
Engineering drawing and Scientific graphics
Analyzing of algorithmic designing and development
Mathematical functions and Computational functions
Simulating problems prototyping and modeling
Application development programming using GUI building environment.