The Journal of Pattern Recognition Research (JPRR) provides an international forum for the electronic publication of high-quality research and industrial experience articles in all areas of pattern recognition, machine learning, and artificial intelligence. JPRR is committed to rigorous yet rapid reviewing. Final versions are published electronically
(ISSN 1558-884X) immediately upon acceptance.
Published Online: An Efficient Skew Estimation Technique for Scanned Documents: An Application of Piece-Wise Painting Algorithm
JPRR Article #635
An efficient skew estimation technique based on Piece-wise Painting Algorithm (PPA) for scanned documents is presented. In PPA, the input image is decomposed into vertical stripes and the gray value of each pixel in each row of a stripe is modified to the average gray value of all pixels present in that row of the stripe. The resultant gray-scale image is then converted into two-tone image which is called painted image. In this research work, we, at first, employ the PPA on the document image horizontally and vertically. Applying the PPA on both directions, two painted images (horizontally and vertically) are obtained. Next, based on statistical analysis some regions from horizontally or vertically painted images are selected. Top (left), middle (middle) and bottom (right) points of horizontal or vertical selected regions are identified in 6 separate lists. Utilizing linear regression of the selected points, a few fit lines are drawn. A voting approach based on statistical mode of angles obtained from fit lines is also proposed to find the best-fit line amongst all the lines and the skew angle of the document image is estimated from the slope of the best-fit line. The proposed technique was tested extensively on three different datasets containing various categories of documents. Comparisons of the results are made with recently published methods when the same datasets are used. Experimental results showed that the proposed technique achieved more accurate results than the state-of-the-art methods.
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Vol 11, No 1 (2016)
An Efficient Skew Estimation Technique for Scanned Documents: An Application of Piece-Wise Painting Algorithm 1-14
In this paper, an effcient skew estimation technique based on iterative employment of the Piece-wise Painting Algorithm (PPA) on document images is presented.
JPRR Vol 11, No 1 (2016); doi:10.13176/11.635
Vol 10, No 1 (2015)
IR Contrast Enhancement Through Log-Power Histogram Modification 1-23
A simple power-logarithm histogram modification operator is proposed to enhance IR image contrast. The algorithm combines a logarithm operator that smoothes the input image histogram while retaining the relative ordering of the original bins, with a power operator that restores the smoothed histogram to an approximation of the original input histogram.
JPRR Vol 10, No 1 (2015); doi:10.13176/11.617
Dynamic Hand Gesture Recognition for Sign Words and Novel Sentence Interpretation Algorithm for Indian Sign Language Using Microsoft Kinect Sensor 24-38
Indian sign language interpretation is an important task to facilitate communication among Indian deaf community and other people.
JPRR Vol 10, No 1 (2015); doi:10.13176/11.626
Fuzzy C-Means With Local Membership Based Weighted Pixel Distance and KL Divergence for Image Segmentation 53-60
This paper presents a new technique for incorporating local membership information into the standard fuzzy C-means (FCM) clustering algorithm.
JPRR Vol 10, No 1 (2015); doi:10.13176/11.605
Multi Cameras Based Indoors Human Action Recognition Using Fuzzy Rules 61-74
In this paper, the recognition of human actions in an indoor work environment using multi cameras is proposed. HOG features learned using AdaBoost and optimized by background differencing are used to detect people, while the overlapping camera views are merged using perspective transformation.
JPRR Vol 10, No 1 (2015); doi:10.13176/11.651
Pattern Recognition Theory
Best Model Classification 39-52
This is about frames of reference for analyzing data and how the frames can be parameterized by measurements of the data. The topic is discussed in terms of a classification method that chooses among alternative frames of reference.
JPRR Vol 10, No 1 (2015); doi:10.13176/11.634