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.
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Published Online: DEMD-based Image Compression Scheme in a Compressive Sensing Framework
JPRR Article #580
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. This is especially true for video image frames in applications such as videos with structural patterns, and Bi-Directional Reflectance Distribution Function (BRDF) image frames of an object, where different images of an object in a single pose are taken in different illumination conditions. This paper investigates a new approach for an efficient representation of a class of images from textured videos and different BRDF images of an object, using sparse representation of the Directional Empirical Mode Decomposition (DEMD) residue of the frame. The efficient representation of the DEMD residue is achieved as a sparse coding solution based on a Discrete Wavelet Transform (DWT)-based sparsification. Experimental results demonstrate the effectiveness of the algorithm showing higher compression as compared to standard wavelet-based image compression schemes in a Compressive Sensing (CS) framework and JPEG2000, at similar perceptual reconstruction quality.
Published Online: Techniques in Pattern Recognition for School Bullying Prevention: Review and Outlook
JPRR Article #586
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 recognition, and activity recognition. This paper reviews some related work and makes some comparisons among these three aspects. The paper analyzes commonly used features and classifiers, and describes some examples. The Gaussian Mixture Model and the Double Threshold classifiers provided high accuracies in many experiments. By using a combined architecture of classifiers, the results could be further improved. According to the results of the experiments, the six basic emotions, high mental stress and irregular movements can be recognized with high accuracies. So the three types of pattern recognition can be used for school bullying detection effectively. And these techniques can be used on consumer devices such as smartphones to protect teenagers.
Published Online: Minimum Manifold-based Within-Class Scatter Support Vector Machine
JPRR Article #565
Although Support Vector Machine 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. In view of this, Minimum Class Variance Support Vector Machine is proposed by Zafeiriou. Compared with SVM, MCVSVM has better generalization ability because it takes both boundary information and distribution characteristics into consideration. While the above mentioned methods SVM and MCVSVM always neglect the local characteristics of each class. Based on the above analysis, this paper presents Minimum Manifold-based Within-Class Scatter Support Vector Machine, which not only focuses on boundary information and distribution characteristics, but also preserves the manifold structure of each class. By theory analysis, M2SVM is equivalent to SVM and MCVSVM in a certain condition. It is believed that compared with SVM and MCVSVM, M2SVM has the best generalization ability. Experiments on the man-made dataset, facial datasets and UCI datasets verify the effectiveness of the proposed method M2SVM.
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
Applications
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
Vol 8, No 1 (2013)
Pattern Recognition Theory
On the Analogy of Classifier Ensembles With Primary Classifiers: Statistical Performance and Optimality 98-122
The question of how we can exploit the ability to combine different learning entities is fundamental to the core of automated pattern analysis and dictates contemporary research efforts in the field of decision fusion.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.497
Applications
A System for Handwritten Script Identification From Indian Document 1-12
In a country like India a number of scripts (a total of 13) are used to write different official languages (a total of 23). For development of Optical Character Recognizer (OCR) for a particular language, the script by which the document is written is to be identified first.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.485
Kernel Non-Negative Matrix Factorization for Seismic Signature Separation 13-25
A supervised learning algorithm for the separation of seismic sources in a single channel is presented. The proposed algorithm employs non-negative matrix factorization (NMF) technique in the feature space, called Kernel NMF (KNMF).
JPRR Vol 8, No 1 (2013); doi:10.13176/11.463
Stereo Disparity and Optical Flow Fusion by Geometric Relationship and an Efficient Recursive Algorithm 26-38
We suggest a relationship, called stereo-motion equation, between stereo disparity and optical flow, and a recursive filter, as an efficient algorithm to estimate the two quantities.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.210
Capped K-NN Editing in Definition Lacking Environments 39-58
While any input may be contributing, imprecise specification of class of data subdivided into classes identifies as rather common a source of noise.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.465
CUES: A New Hierarchical Approach for Document Clustering 66-84
Objective of the document clustering techniques is to assemble similar documents and segregate dissimilar documents. Unlike document classification, no labeled documents are provided in document clustering.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.459
An Image Visual Quality Assessment Method Based on SIFT Features 85-97
There are a number of distortions in image acquisition, processing, compression, storage, transmission, and reproduction. Existing image metrics provide a good judgement on these image distortions.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.511
Dismount Detection Using Kernel Sparse Representation 123-131
This paper describes a new application of kernel sparse detection technique for hyperspectral imagery (HSI) in conjunction with a sequential forward feature selection (SFFS) scheme that reduces the dimensionality to a tractable volume.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.528
Short Letters
Some Features of the Users' Activities in the Mobile Telephone Network 59-65
JPRR Vol 8, No 1 (2013); doi:10.13176/11.517