Skew Thresholding

Abstract- Ancient documents accumulate a significant amount of human heritage over time. However, many environmental factors, improper handling, and the poor quality of the materials used in their creation cause them to suffer a high degree of degradation of various types. There are lots of ancient documents which are badly degraded. It is very difficult to segment text from the document, as there is a variation between the document background and foreground. Binarization technique that addresses these issues using adaptive image contrast and its related features is highly concerned for research purpose in image processing. There are mainly three feature on the basis of the phase information of an input document image constitute the core of

Thresholding has created to be a well-known technique used for binarization of document images. Thresholding is further divide into the global and local thresholding technique. Noise reduction:
The noise, introduced by the optical scanning device or the writing instrument, causes disconnected line segments, bumps and gaps in lines, filled loops etc. The distortion including local variations, rounding of corners, dilation and erosion, is also a problem. Prior to the character recognition, it is necessary to eliminate these imperfections .
Skew Detection and Correction:
Handwritten document may originally be skewed or skewness may introduce in document scanning process. This effect is unintentional in many real cases, and it should be eliminated because it dramatically reduces the accuracy of the subsequent processes, such as segmentation and classification. Skewed lines are made horizontal by calculating skew angle and making proper correction in the raw image. Thinning:
The boundary detection of image is done to enable easier subsequent detection of pertinent features and objects of interest.[6]

II. IMAGE

Scanning and printing of documents can degrades their visibility that means it become difficult to understand them. Image binarization is the process of separation of pixel values into dual collections, black as foreground and white as background. Thresholding has created to be a well-known technique used for binarization of document images. Thresholding is further divide into the global and local thresholding technique. In document with uniform contrast delivery of background and foreground, global thresholding is has found to be best technique. In degraded documents, where extensive background noise or difference in contrast and brightness exists i.e. there exists many pixels that cannot be effortlessly categorized as foreground or background. In such cases, local thresholding has significant over available techniques. Its goal is to segment the pixels on the document image into just two classes, regardless of the enormous number of possible text typefaces and the vari- ous types of degradation, which make it an ambitious process. Therefore, document image binarization is of great importance in the document image analysis and recognition pipeline since it affects further stages of the recognition