Skew Angle Detection of Bangla Script using Radon Transform

Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318), 1999

In this paper, a range free skew detection technique for machine printed Gurmukhi documents has been presented. This approach can easily be extended to other Indian language scripts such as Devnagri and Bakngla. Most characters in these scripts have horizontal lines at the top called headlines. The characters forming a word are joined at top by headlines, so that the word appears as one single component with headline. The ratio of pixel density above and below the headline of any word in Gurmukhi script is always less than 1. These inherent characteristics of the script have been employed and a new algorithm based on projection profile method has been devised. By inspecting horizontal and vertical projections at different angles in range [0°, 90°], the skew angle of the document in range [-180°, 180°] can be determined. Thus this approach is not limited to any range of skew angle and skewness in any document with orientation portrait or landscape and placed at any angle can easily be detected and removed.

A major problem of pattern recognition is the Optical Character Recognition (OCR) especially for Hindi Handwritten Documents. In this paper we attempt to face common problems of handwritten documents such as nonparallel text lines in a page, slanted and connected characters. Towards this end an integrated system for handwritten Hindi document preprocessing is presented. This system consists of the following modules: skew angle detection, line and word segmentation, slope correction and slant Removal. The skew angle correction, slope correction and slant removing algorithms are based on a novel algorithm which is tested on various Handwritten Hindi Document images. Our system can be used as a preprocessing stage to any handwriting character recognition or segmentation system as well as to any writer identification system.

Pattern Recognition Letters, 1996

When a document is fed to a scanner either mechanically or by a human operator for digitization, it suffers from some degrees of skew or flit. Skew angle detection is an important component of any Optical Character Recognition (OCR) and document analysis system. In this letter we consider skew estimation of Roman script. The method considers the lowermost and uppermost pixels of some selected characters of the text which may be subject to Hough transform for skew angle detection. A fast approach is also proposed which works almost as accurately as Hough transform. Experimental results are presented and compared with results on several other skew detection methods.

2012 IEEE Student Conference on Research and Development (SCOReD), 2012

Optical Character Recognition has been a challenging field in the advent of digital computers. It is needed where information is to be readable both to humans and machines. The process of OCR is composed of a set of pre and post processing steps that decide the level of accuracy of recognition. This paper deals with one of the pre-processing steps involved in the OCR process i.e. Skew (Slant) Detection and Correction. The proposed algorithm implemented for skew-detection is termed as the COG (Centre of Gravity) method and for that of skew-correction is Sub-Pixel Shifting method. The algorithm has been kept simple and optimized for efficient skew-detection and correction. The performance analysis of the algorithm after testing has been aptly demonstrated.

DAAAM Proceedings, 2018

This paper proposes the framework and implemented algorithm for text skew angle detection and auto correction of scanned documents. The process of scanning the documents might cause their displacement and rotation, which later affects the difficulty in text recognition process. The paper presents a developed application with the algorithm adapted specially for the framework. The implemented algorithm is based on Fast Fourier Transform. The framework enables text skew angle measurement and according to the archived results performs rotation and correction of the scanned document. Evaluation of the framework was focused on determining accuracy in skew angle detection, on determining the implemented algorithm sensitivity based on the resolution and quality of scanned documents. The evaluation showed that the proposed framework achieved good results which provide guidance for the further development of similar frameworks.

ijmlc.org

The performance of an OCR system will not be satisfactory for most of the scanned images without accurate skew correction. This paper presents the skew angle estimation and correction for Urdu document images script using moments method. The basic idea is to draw a random polygon over the text in document. This leads to thinning free preprocessing. The skew angle is calculated using Central moments and centroid of the document image. Experimental results are found to be satisfactory and compared with other skew detection techniques.

International Conference on Computer Graphics, Imaging and Visualization (CGIV'05), 2000

Optical Character Recognition (OCR) is an area which has always received special attention. OCR systems are typically built on the strategy of divide and conquer, rather than recognizing documents at one go. They utilize several stages during the course of recognition. There have been many stages in a typical OCR system, preprocessing stage in considered to be indispensable. An input image or information need to be normalized and converted into format acceptable by OCR system. OCR systems typically assume that documents were printed with a single direction of the text and that the acquisition process did not introduce a relevant skew. Practically this assumption is not very strong and printed document could be skewed at some angle with horizontal axis. In this paper, we have proposed a new technique for skew estimation of image document. In the proposed scheme, multiscale properties of an image are utilized together with Principal Component Analysis to estimate the orientation of principal axis of clustered data.

2012 Third International Conference on Emerging Applications of Information Technology, 2012

Skewness in the handwritten document images is a common scenario. Therefore, it is very much required to detect and correct the skewness before the document is presented to the document image analysis system. In this regard, the present work develops a two-stage Hough transform based approach to remove the skewness in the document images written in Bangla script. Firstly, page-level skewness is removed by rotating the skewed text lines appropriately and then skewed words in each text line, if any, are also rotated along a reference line.

2016

Document image processing has become an increasingly important technology in the automation of office documentation tasks. Automatic document scanners such as text readers and OCR (Optical Character Recognition) systems are an essential component of systems capable of those tasks. One of the problems in this field is that the document to be read is not always placed correctly on a flatbed scanner. This means that the document may be skewed on the scanner bed, resulting in a skewed image. This skew has a detrimental effect on document analysis, document understanding, and character segmentation and recognition. Consequently, detecting the skew of a document image and correcting it are important issues in realizing a practical document reader. Very frequently the digitalization process of documents produce images rotated of small angles in relation to the original image axis. In this paper we present a review on various skew detection and correction techniques.

2009 IEEE 5th International Conference on Intelligent Computer Communication and Processing (ICCP 2009), 2009

This paper describes an approach towards an orientation and skew detection for texts in scanned documents. Before using OCR systems to obtain character information from images, a preprocessing stage, comprising a number of adjustments, has to be performed in order to obtain accurate results. One important operation that has to be considered is the skew correction, or deskewing, of the image, a fault that arises from an incorrect scanning process. This paper presents an iterative method for detecting the text orientation and skew angle, method based on histogram processing.