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.
Special Issue Announcement - Submission Deadline ExtendedHybrid Soft Computing for Pattern Recognition and Image Analysis

Many real life problems suffer from uncertainty, imprecision, vagueness to name a few. Conventional computing paradigms often fall short of offering solutions to them. Even latest soft computing paradigms are not too robust to handle the situations. Hybrid soft computing is a paradigm which addresses these issues to a considerable extent.

This special issue on hybrid soft computing for pattern recognition and image analysis intends to bring together researchers to report the latest results and progress in the development of hybrid soft computing paradigm for faithful pattern recognition and image analysis. As such, the focus of this special issue is the methods of Computational Intelligence, with a focus on hybrid soft computing methods applied to pattern recognition research. The fields under consideration encompass a wide range of applications.

Published Online: Boosting Shape Classifiers Accuracy by Considering the Inverse Shape
JPRR Article #727
Many techniques exist for describing shapes. These techniques almost exclusively consider the contour or the inside of the shape; the major problem for describing the outside of a shape, or inverse shape, being that it has an infinite extension. In this paper, we show how to adapt two shape descriptors , one region based, the Cover By Rectangles, and one transform based, the Zernike moments, to be applicable to the inverse shape. We analyze their properties, and show how to deal with the infinite extension of the inverse shape. Then, we apply these descriptors to shape classification and compare representations that use the shape, its inverse, or both. Our experiments establish that, for shape classification, a representation integrating the inverse shape often outperforms a representation restricted to the shape. This opens the path for better techniques that could use, as a rule of thumb, both the representations of a shape and its inverse for the purpose of classification.
JPRR selected for the Emerging Sources Citation Index (ESCI)

We are pleased to announce that the Journal of Pattern Recognition Research (JPRR) has been selected for coverage in Thomson Reuters products and services. Beginning with content published in 2015, this publication will be indexed and abstracted in Emerging Sources Citation Index (ESCI).

JPRR's content in ESCI is under consideration by Thomson Reuters for inclusion in products such as the Science Citation Index Expanded™ (SCIE), the Social Sciences Citation Index® (SSCI), and the Arts & Humanities Citation Index® (AHCI).

Read the journal's most cited open-access articles online! Submit your next article to JPRR!

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
A Brief Review of Human Identification Using Eye Movement 15-25
The vulnerability of conventional biometrics to spoof has caused considerable concern especially in those fields that require high reliable user identification.
JPRR Vol 11, No 1 (2016); doi:10.13176/11.705
Application of Approximate Equality for Reduction of Feature Vector Dimension 26-40
Reduction of feature vector dimension is a problem of selecting the most informative features from an information system. Using rough set theory we can reduce the feature vector dimension when all the attribute values are crisp or discrete.
JPRR Vol 11, No 1 (2016); doi:10.13176/11.639
Pattern Recognition Theory
Boosting Shape Classifiers Accuracy by Considering the Inverse Shape 41-54
Many techniques exist for describing shapes. These techniques almost exclusively consider the contour or the inside of the shape; the major problem for describing the outside of a shape, or inverse shape, being that it has an infinite extension.
JPRR Vol 11, No 1 (2016); doi:10.13176/11.727
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