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.
Article In Press: Fuzzy C-Means with Local Membership Based Weighted Pixel Distance and KL Divergence for Image Segmentation
JPRR Article #605
This paper presents a new technique for incorporating local membership information into the standard fuzzy C-means (FCM) clustering algorithm. In this technique, the objective consists of minimizing the classical FCM function with a unity fuzzification exponent plus a weighted proposed fuzzification and regularization term. The pixel to cluster-center distance is weighted using the reciprocal of the local membership average. The regularization term is formulated using the Kullback-Leibler (KL) divergence which measures the proximity between a pixel membership and the local average of this membership in the immediate neighborhood. Therefore, minimizing this KL divergence biases the cluster membership of the pixel toward the local membership average. It is also shown that the proposed weighted distance further leads to assigning a pixel to the cluster more likely existing in the immediate neighborhood. This can provide immunity against noise and results in clustered images with piecewise homogeneous regions. Results of clustering and segmentation of synthetic and real-world images are presented to compare the performance of the proposed local membership based weighted distance and KL divergence FCM (LMWDKLFCM) and the standard FCM, a local data based information FCM (LDMFCM) and a type of local membership information based FCM (LMFCM) algorithms.
Published Online: Best Model Classification
JPRR Article #634
This paper is about frames of reference and their relation to classification. A classification is needed to establish a frame of reference and, with a frame of reference, measurements and further classifications are possible. The topic is discussed in terms of a method that chooses the “best” among alternative frames of reference. We will describe how measurements induce a fiber bundle that projects from a total space of objects onto a base space of measurement values. Local inverses of this projection, or “sections” of the fiber bundle play the role of frames of reference or ideal objects that are attached to the data, as the nearest neighbor in the fiber. In this formalism the invariant properties of personality are parameterized by the variant ones, which are measured, and classification is seen as inverse to measurement. Rather than proving theorems, the article has a two goals: to provide engineers with a recipe for solving classification problems; and to bring the concept of moving frames from differential geometry into a broader discussion of classification.
JPRR welcomes Dr. Weihua Sun as a Prospective Associate Editor
Dr. Weihua SunDr. Weihua Sun, Motorola
Dr. Weihua Sun received his PhD degree from the Center for Imaging Science at Rochester Institute of Technology. He is currently working as an imaging engineer in Motorola Mobility focusing on algorithm development for imaging applications. His research interests are imaging science, image processing, pattern recognition, machine learning, image quality, remote sensing and multispectral and hyperspectral imaging. He also has MS and BS degrees in physics from Nanjing University, where his research area was design, simulation, and fabrication of optical metamaterials.
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
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
Vol 9, No 1 (2014)
Pattern Recognition Theory
Speed-Up Template Matching Through Integral Image Based Weak Classifiers 1-12
Template matching is a widely used pattern recognition method, especially in industrial inspection. However, the computational costs of traditional template matching increase dramatically with both template-and scene imagesize.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.516
Minimum Manifold-Based Within-Class Scatter Support Vector Machine 79-89
Although Support Vector Machine (SVM) is widely used in practice, it only takes the boundary information between classes into consideration while neglects the data distribution, which seriously limits the classification efficiency.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.565
Randomized Algorithm for Approximate Nearest Neighbor Search in High Dimensions 111-122
A randomized algorithm employs a degree of randomness as part of its logic with uniform random bits as an auxiliary input to guide its behavior, in the hope of achieving good average runtime performance over all possible choices of the random bits.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.599
Direct Inverse Randomized Hough Transform for Incomplete Ellipse Detection in Noisy Images 13-24
A direct inverse randomized Hough transform (DIRHT) is developed as a pre-processing procedure for incomplete ellipse detection in images with strong noise.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.512
Virtual DMA Municipal Water Supply Pipeline Leak Detection and Classification Using Advance Pattern Recognizer Multi-Class SVM 25-42
In this paper we investigated and analyzed the concept of virtual DMA as the core objective of the research to resolve the current Gap and limitations of the DMA state of practice through the development of Virtual DMA Leakage Monitoring and Classification System Using Multi-class Support Vector Machine (SVM) Advanced Pattern Recognizer at Lille University WDS study area the so called “Zone-6”.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.548
Machine Learning Based Acoustic/IR Monitoring 43-49
Chiropteran monitoring has become an important public concern given that wind turbines pose the threat of injury or death to bats through direct impact or barotraumas.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.594
Techniques in Pattern Recognition for School Bullying Prevention: Review and Outlook 50-63
School bullying is a serious problem among teenagers. With the development of sensor technology and pattern recognition algorithms, several approaches for detecting school bullying have been developed, namely speech emotion recognition, mental stress recog- nition, and activity recognition.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.586
DEMD-Based Image Compression Scheme in a Compressive Sensing Framework 64-78
Efficient representation of the background texture in video image frames, motivates compression strategies based on good perceptual reconstruction quality, instead of just bit-accurate reconstruction.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.580
2-D Shapes Description by Using Features Based on the Differential Turning Angle Scalogram 90-110
A 2-D shape description using the turning angle (or tangential angle) is presented . This representation is based on a scalogram obtained from a progressive filtering of a planar closed contour of an object.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.571
A Body Part Segmentation System for Human Activity Recognition in Videos 123-137
Identification of body parts is an important first step for many tasks such as action recognition in automatic surveillance systems.
JPRR Vol 9, No 1 (2014); doi:10.13176/11.611