Search Word(s) in Title, Keywords, Authors, and Abstract: Pattern Recognition

Novel Approaches for Applying Linguistic Processing Techniques Based on Pattern Recognition and Machine Learning
Jong Hyuk Park
Page: 643~652, Vol. 13, No.4, 2017
10.3745/JIPS.00.0006

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The Journal of Information Processing Systems (JIPS) publishes a broad array of subjects related to information communication technology in a wide variety of prevalent and advanced fields, including systems, networks, architecture, algorithms, applications, security, and so forth. As the official international journal published by the Korean Information Processing Society and a prominent, multidisciplinary journal in the world, JIPS is indexed in ESCI, SCOPUS, EI COMPENDEX, DOI, DBLP, EBSCO, Google Scholar, and CrossRef. The purpose of JIPS is to provide a prominent, influential forum where researchers and professionals can come together to promote, share, and discuss all major research issues and developments. Published theoretical and practical articles contribute to their related research areas by presenting new techniques, concepts, or analyses, and feature experience reports, experiments involving the implementation and application of new theories, and tutorials on state-of-the-art technologies related to information processing systems. The subjects covered by this journal include, but are not limited to, topics related to computer systems and theories, multimedia systems and graphics, communication systems and security, and software systems and applications.


Efficient Approaches to Computer Vision and Pattern Recognition
Jong Hyuk Park
Page: 1043~1051, Vol. 13, No.5, 2017
10.3745/JIPS.00.0007

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The Journal of Information Processing Systems (JIPS) publishes a wide range of topics related to a wide variety of advanced information and communication technologies, including systems, networks, architectures, algorithms, applications, and security. JIPS is the official international journal published by the Korea Information Processing Society and is the world's leading academic journal indexed by ESCI, SCOPUS, EI COMPENDEX, DOI, DBLP, EBSCO, Google Scholar, and CrossRef. The purpose of JIPS is to provide an outstanding, influential forum where researchers and experts gather to promote, share, and discuss crucial research issues and developments. The published theoretical and practical articles contribute to the relevant research area by presenting cutting-edge techniques related to information processing including new theories, approaches, concepts, analysis, functional experience reports, implementations, and applications. Topics covered in this journal include, but are not limited to, computer systems and theory, multimedia systems and graphics, communication systems and security, software systems, and applications.


Efficient Approaches to Computer Vision and Pattern Recognition
Jong Hyuk Park
Page: 1431~1435, Vol. 13, No.6, 2017
10.3745/JIPS.00.0008

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The Journal of Information Processing Systems (JIPS) is one of the journals published by the Korean Information Processing Society (KIPS), which publishes papers related to a wide variety of advanced research fields including systems, applications, networks, architecture, algorithms, security, and so forth. The organization and has the indices such as ESCI, SCOPUS, EI COMPENDEX, DOI, DBLP, EBSCO, Google Scholar, and CrossRef. There are four divisions: Computer System and Theory, Multimedia Systems and Graphics, Communication Systems and Security, and Information Systems and Application.


Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis
Leila Boussaad, Mohamed Benmohammed and Redha Benzid
Page: 392~409, Vol. 12, No.3, 2016
10.3745/JIPS.02.0043

Keywords: Active Appearance Model, Age-Invariant, Face Recognition, Kernel Fisher Analysis, 2D-Discrete Cosine Transform
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The aim of this paper is to examine the effectiveness of combining three popular tools used in pattern recognition, which are the Active Appearance Model (AAM), the two-dimensional discrete cosine transform (2D-DCT), and Kernel Fisher Analysis (KFA), for face recognition across age variations. For this purpose, we first used AAM to generate an AAM-based face representation; then, we applied 2D-DCT to get the descriptor of the image; and finally, we used a multiclass KFA for dimension reduction. Classification was made through a K-nearest neighbor classifier, based on Euclidean distance. Our experimental results on face images, which were obtained from the publicly available FG-NET face database, showed that the proposed descriptor worked satisfactorily for both face identification and verification across age progression.


Adaptive Cross-Device Gait Recognition Using a Mobile Accelerometer
Thang Hoang, Thuc Nguyen, Chuyen Luong, Son Do and Deokjai Choi
Page: 333~348, Vol. 9, No.2, 2013
10.3745/JIPS.2013.9.2.333
Keywords: Gait Recognition, Mobile Security, Accelerometer, Pattern Recognition, Authentication, Identification, Signal Processing
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Mobile authentication/identification has grown into a priority issue nowadays because of its existing outdated mechanisms, such as PINs or passwords. In this paper, we introduce gait recognition by using a mobile accelerometer as not only effective but also as an implicit identification model. Unlike previous works, the gait recognition only performs well with a particular mobile specification (e.g., a fixed sampling rate). Our work focuses on constructing a unique adaptive mechanism that could be independently deployed with the specification of mobile devices. To do this, the impact of the sampling rate on the preprocessing steps, such as noise elimination, data segmentation, and feature extraction, is examined in depth. Moreover, the degrees of agreement between the gait features that were extracted from two different mobiles, including both the Average Error Rate (AER) and Intra-class Correlation Coefficients (ICC), are assessed to evaluate the possibility of constructing a device-independent mechanism. We achieved the classification accuracy approximately 91.33 ± 0.67 % for both devices, which showed that it is feasible and reliable to construct adaptive cross-device gait recognition on a mobile phone.


Fingerprint Detection Using Canny Filter and DWT, a New Approach
Md. Imdadul Islam, Nasima Begum, Mahbubul Alam and M. R. Amin
Page: 511~520, Vol. 6, No.4, 2010
10.3745/JIPS.2010.6.4.511
Keywords: Canny Filter, Color Inversion, Skewness, Kurtosis and Convolution
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This paper proposes two new methods to detect the fingerprints of different persons based on one-dimensional and two-dimensional discrete wavelet transformations (DWTs). Recent literature shows that fingerprint detection based on DWT requires less memory space compared to pattern recognition and moment-based image recognition techniques. In this study four statistical parameters - cross correlation co-efficient, skewness, kurtosis and convolution of the approximate coefficient of one-dimensional DWTs are used to evaluate the two methods involving fingerprints of the same person and those of different persons. Within the contexts of all statistical parameters in detection of fingerprints, our second method shows better results than that of the first method.