Skew detection and correction of mushaf Al-Quran script using hough transform

Document skew detection and correction is mainly one of base preprocessing steps in the document analysis. Correction of the skewed scanned images is critical because it has a direct impact on image quality. In this paper, the authors proposed a method for skew detection and correction for Mushaf Al-Quran image pages based on Hough transform method. The technique uses Hough transform lines detection for calculating the skew angulation. It works for different version of Mushaf AlQuran image pages which has skewed text zones. Moreover, it can detect and correct the skew angle in the range between 20 degrees. Experiment conducted on different Mushaf Al-Quran image pages shows the accuracy of the method

Skew Detection and Correction in Scanned Document Images.

During document scanning, skew is inevitably introduced into the incoming document image. Skew detection is one the first operations to be applied to scanned documents when converting data to a digital format. Its aim is to align an image before processing because text segmentation and recognition methods require properly aligned next lines. Different algorithms of skew detection are implemented. The first one is Scan line based skew detection. In this method the image is projected at several angles and the variance in the number of black pixels per projected scan line is determined. The angle at which the maximum variance occurs is the angle of skew.The second one is based on the Hough transform. Hough transform is performed on the scanned document image and the variance in ρ values is calculated for each value of θ. The angle that gives the maximum variance is the skew angle.The third approach is based on the base-point method. Here a concept of basepoint is introduced. After the successive base-points in every text line within a suitable sub-region were selected as samples for the straight-line fitting. The average of these baseline directions is computed, which corresponds to the degree of skew of the whole document image.All the above mentioned algorithm have been implemented and the results of each have been compared for accuracy

Skew Detection And Correction Of Mushaf Al-Quran Script Using Hough Transform

Document skew detection and correction is mainly one of base preprocessing steps in the document analysis. Correction of the skewed scanned images is critical because it has a direct impact on image quality. In this paper, the authors proposed a method for skew detection and correction for Mushaf Al-Quran image pages based on Hough transform method. The technique uses Hough transform lines detection for calculating the skew angulation. It works for different version of Mushaf Al-Quran image pages which has skewed text zones. Moreover, it can detect and correct the skew angle in the range between 20 degrees. Experiment conducted on different Mushaf Al-Quran image pages shows the accuracy of the method

Estimation of the Handwritten Text Skew Based on Binary Moments

Binary moments represent one of the methods for the text skew estimation in binary images. It has been used widely for the skew identification of the printed text. However, the handwritten text consists of text objects, which are characterized with different skews. Hence, the method should be adapted for the handwritten text. This is achieved with the image splitting into separate text objects made by the bounding boxes. Obtained text objects represent the isolated binary objects. The application of the moment-based method to each binary object evaluates their local text skews. Due to the accuracy, estimated skew data can be used as an input to the algorithms for the text line segmentation

Kannada Character Recognition System A Review

Intensive research has been done on optical character recognition ocr and a large number of articles have been published on this topic during the last few decades. Many commercial OCR systems are now available in the market, but most of these systems work for Roman, Chinese, Japanese and Arabic characters. There are no sufficient number of works on Indian language character recognition especially Kannada script among 12 major scripts in India. This paper presents a review of existing work on printed Kannada script and their results. The characteristics of Kannada script and Kannada Character Recognition System kcr are discussed in detail. Finally fusion at the classifier level is proposed to increase the recognition accuracy.Comment: 12 pages, 8 figure

Use of colour for hand-filled form analysis and recognition

Colour information in form analysis is currently under utilised. As technology has advanced and computing costs have reduced, the processing of forms in colour has now become practicable. This paper describes a novel colour-based approach to the extraction of filled data from colour form images. Images are first quantised to reduce the colour complexity and data is extracted by examining the colour characteristics of the images. The improved performance of the proposed method has been verified by comparing the processing time, recognition rate, extraction precision and recall rate to that of an equivalent black and white system