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Gait recognition with Transient binary patterns

JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2015年第Nov.期33卷 69-77页

作者： Lee, Chin Poo Tan, Alan W. C. Tan, Shing Chiang Multimedia Univ Fac Informat Sci & Technol Melaka 75450 Malaysia Multimedia Univ Fac Engn & Technol Melaka 75450 Malaysia

In this work, we present a combination of spatiotemporal approach and texture descriptors to extract the temporal patterns in gait cycles. Unlike most conventional methods that focus on spatial information while limiting temporal information captured, spatiotemporal methods preserve both spatial and temporal information. Inspired by the success of texture descriptors in face recognition, the proposed method likewise constructs texture descriptors of gait motion over time. For each gait cycle, the pixel-wise binary patterns along the temporal axis, referred to as the Transient binary patterns (TBP), is analyzed. These pixel-wise TBPs are then grouped into regional blocks from which we construct regional TBP histograms. These regional TBP histograms collectively form the global TBP histogram that represents both the distribution of temporal patterns and spatial location. Experimental results clearly show the superiority of the proposed approach over other considered methods. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Gait recognition Gait Human walking Transient binary patterns binary patterns Texture Texture descriptor Histograms

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Evaluation of activity from binary patterns in dynamic speckle analysis

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OPTICS AND LASERS IN ENGINEERING 2018年 111卷 50-57页

作者： Stoykova, Elena Kang, Hoonjong Kim, Youngmin Nazarova, Dimana Nedelchev, Lian Ivanov, Branimir Berberova, Natalia Mateev, Georgi Korea Elect Technol Inst VR AR Res Ctr 8 Floor11 World Cup Buk Ro 54 Gil Seoul South Korea Bulgarian Acad Sci Inst Opt Mat & Technol Acad G Bonchev StrBl 109POB 95 Sofia 1113 Bulgaria

Pointwise intensity-based statistical processing of dynamic laser speckle patterns formed on the surface of a diffusely reflecting object is perspective for monitoring of ingoing processes of physical or biological activity within the object. The output of the measurement is a two-dimensional map, which shows qualitatively regions of higher or lower activity on the object surface. In the paper, we have proposed transforming the captured 8-bit encoded speckle patterns into binary patterns by applying a pointwise threshold. Motivation behind this study is the need for an algorithm, which is robust to non-uniform illumination and offers lowered computational complexity as time and memory consumption. We showed by simulation and experiment that quality of the map obtained by processing of correlated binary patterns approached that achieved with 8-bit encoded patterns. We analyzed statistical behavior of the estimates built from binary patterns and proved applicability of a non stochastic threshold as e.g. a constant intensity level at uniform illumination. The proposed algorithm was applied for processing polymer drop drying experimental data.

关键词： Dynamic speckle Correlation-based processing binary patterns Speckle metrology

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DESIGN OF A RANDOM-PULSE COMPUTER FOR CLASSIFYING binary patterns

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IEEE TRANSACTIONS ON COMPUTERS 1972年第12期C 21卷 1347-1354页

作者： GOKE, LR DOTY, KL UNIV FLORIDA DEPT ELECT ENGNGAINESVILLEFL 32601

This paper proposes a novel design for a parallel nonadaptive binary pattern classifier. The structure employs random-pulse (stochastic) computing elements to economically realize multimodal nonlinear discriminant functions similar in form to those used in potential function classifiers. The technique achieves efficient hardware utilization by employing a READ-ONLY memory (ROM) without addressing circuits to store modes and simultaneously execute parallel stochastic multiplications required in discriminant function computations.

关键词： binary patterns discriminant functions nonadaptive nonlinear pattern recognition random-pulse computing stochastic computing.

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MATRIX TRANSFORMATIONS FOR N-TUPLE ANALYSIS OF binary patterns

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IEEE TRANSACTIONS ON COMPUTERS 1976年第5期25卷 542-546页

作者： RATZ, HC UNIV WATERLOO DEPT ELECT ENGNWATERLOOONTARIOCANADA

The frequency of occurrence of logic functions of binary N-tuples can be observed from sequences of binary patterns. The logic functions considered here are AND, NOR, NAND, OR, and an odd-even parity check; and the frequency parameters are expressed as real matrix transformations on the probabilities of the patterns. Some properties, inverses, and interrelationships among the parameter sets are given, along with fast algorithms to facilitate computational processes. The results permit the outputs of convenient hardware logic operations to be converted into other parameters for smoothing, detection, or inference purposes, or to estimate the pattern probabilities by inversion. A measure of association among binary patterns is given as one characteristic feature which can be derived from the observed parameters.

关键词： binary patterns conditional expectation fast algorithms matrix transformations N-tuple analysis pattern association measure

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Image Encryption Using Genetic Algorithm and binary patterns

Image Encryption Using Genetic Algorithm and Binary Patterns

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10th International ISC Conference on Information Security and Cryptology (ISCISC)

作者： Afarin, Roza Mozaffari, Saeed Islamic Azad Univ Qazvin Branch Elect & Comp Engn Dept Qazvin Iran Semnan Univ Elect & Comp Engn Dept Semnan Iran

ISBN: (纸本)9781479916382

The aim of this paper is image encryption using Genetic algorithm (GA). The proposed encryption method consists of two phases. In substitution phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the modification phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For substitution phase, these binary patterns are generated by Local binary Pattern (LBP) operator while for modification phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. Because it is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 and 1 to 0 in LBP image and histogram uniformity in substitution and modification phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

关键词： Image encryption Genetic algorithm binary patterns

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An algorithm to detect linearly separable clusters of binary patterns

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Pattern Recognition 1979年第2期11卷 109-114页

作者： Warnekar, C.S. Krishna, G. Electrical Engineering Department Indian Institute of Science Bangalore 560012 India

The clusters of binary patterns can be considered as Boolean functions of the (binary) features. Such a relationship between the linearly separable (LS) Boolean functions and LS clusters of binary patterns is examined. An algorithm is presented to answer the questions of the type: "Is the cluster formed by the subsets of the (binary) data set having certain features AND/NOT having certain other features, LS from the remaining set?" The algorithm uses the sequences of Numbered binary Form (NBF) notation and some elementary (NPN) transformations of the binary data. © 1979.

关键词： binary patterns Cluster Convexity Linear separability Numbered binary form Ordered sequence

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Keypoint Detection in RGB-D Images Using binary patterns 2nd

Keypoint Detection in RGB-D Images Using Binary Patterns

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2nd Iberian Robotics Conference (ROBOT)

作者： Romero-Gonzalez, Cristina Martinez-Gomez, Jesus Garcia-Varea, Ismael Rodriguez-Ruiz, Luis Univ Castilla La Mancha Comp Syst Dept Campus Univ S-N Albacete 02071 Spain Univ Alicante Comp Sci & Artificial Intelligence Dept POB 99 E-03080 Alicante Spain

ISBN: (纸本)9783319271491;9783319271484

Detection of keypoints in an image is a crucial step in most registration and recognition tasks. The information encoded in RGB-D images can be redundant and, usually, only specific areas in the image are useful for the classification process. The process of identifying those relevant areas is known as keypoint detection. The use of keypoints can facilitate the following stages in the image processing process by reducing the search space. To properly represent an image by means of a set of keypoints, properties like repeatability and distinctiveness have to be fullfilled. In this work, we propose a keypoint detection technique based on the Shape binary Pattern (SBP) descriptor that can be computed from RGB-D images. Next, we rely on this method to identify the most discriminative patterns that are used to detect the most relevant keypoint. Experiments on a well-know benchmark for 3D keypoint detection have been performed to assess our proposal.

关键词： Keypoint detection RGB-D images binary patterns Local descriptors Shape binary pattern

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Hybrid methodology focused on the model of binary patterns and the theory of fuzzy logic for facial biometric verification and identification 7

Hybrid methodology focused on the model of binary patterns a...

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7th International Joint Conference on Computational Intelligence, IJCCI 2015

作者： Nava, Sergio González Silva, Alberto J. Rosales Montiel, Nidiyare Hevia Funes, Francisco J. Gallegos González, Mario Dehesa Escuela Superior de Ingenieria Mecánica y Eléctrica Instituto Politécnico Nacional Zacatenco Ciudad de México Mexico Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas Universidad Nacional Autónoma de México Mexico

ISBN: (纸本)9789897581571

It is proposed a methodology to improve verification and identification biometric facial indicators based in hybridization binary pattern models and the fuzzy logic theory, making besides use of the traditional image pre-procebing models, feature extraction and clabifiers to validate the performance of the proposal methodology. The facial recognition is complicated due to the variability of the facial appearance related the same person, and the small characteristic samples for each person in adverse conditions. To fix this, is considered the binary pattern models as an excellent choice to the local face representations, whose more important properties is their tolerance against the variations of luminance, scale and rotation. However, the binary pattern model is sensitive to small variations of the pixel intensities, generally caused by the noise, which introduce uncertainty to the texture and contrast representation of the facial image. Using fuzzy logic in the binary patterns calculation, leads to a texture representation model that takes into account the uncertainty of the contained information in each image, providing a better representation of texture and contrast measure. In combination with traditional algorithms in the pre-procebing stage, as photometric and histogram normalization, the feature extraction stage is achieved using linear discriminants and Gabor wavelets to provide finally a stage of the support vector machines clabification. © Copyright 2015 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： binary patterns Facial Biometrics Fuzzy Logic Image Procebing Pattern Recognition

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Using binary patterns for Counting Falsifying Assignments of Conjunctive Forms

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ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE 2015年 315卷 17-30页

作者： De Ita Luna, Guillermo Raymundo Marcial-Romero, J. Pozos-Parra, Pilar Hernandez, Jose A. Benemerita Univ Autonoma Puebla Fac Ciencias Computac Puebla Mexico Univ Autonoma Estado Mexico Fac Ingn Toluca Mexico Univ Juarez Autonoma Tabasco Div Acad Informat & Sistemas Tabasco Mexico

The representation of the set of falsifying assignments of clauses via binary patterns has been useful in the design of algorithms for solving #FAL (counting the number of falsifying assignments of conjunctive forms (CF)). Given as input a CF formula F expressed by m clauses defined over n variables, we present a deterministic algorithm for computing #FAL(F). Principally, our algorithm computes non-intersecting subsets of falsifying assignments of F until the space of falsifying assignments defined by F is covered. Due to #SAT(F) = 2(n)-#FAL(F), results about #FAL can be established dually for #SAT. The time complexity of our proposals for computing #FAL(F) is established according to the number of clauses and the number of variables of F.

关键词： #SAT #FAL binary patterns Enumerative Combinatorics

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Uncovering Non-random binary patterns Within Sequences of Intrinsically Disordered Proteins

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JOURNAL OF MOLECULAR BIOLOGY 2022年第2期434卷 167373-167373页

作者： Cohan, Megan C. Shinn, Min Kyung Lalmansingh, Jared M. Pappu, Rohit, V Washington Univ Dept Biomed Engn St Louis MO 63130 USA Washington Univ Ctr Sci & Engn Living Syst CSELS St Louis MO 63130 USA Washington Univ Dept Phys St Louis MO 63130 USA

Sequence-ensemble relationships of intrinsically disordered proteins (IDPs) are governed by binary patterns such as the linear clustering or mixing of specific residues or residue types with respect to one another. To enable the discovery of potentially important, shared patterns across sequence families, we describe a computational method referred to as NARDINI for Non-random Arrangement of Residues in Disordered Regions Inferred using Numerical Intermixing. This work was partially motivated by the observation that parameters that are currently in use for describing different binary patterns are not interoperable across IDPs of different amino acid compositions and lengths. In NARDINI, we generate an ensemble of scrambled sequences to set up a composition-specific null model for the patterning parameters of interest. We then compute a series of pattern-specific z-scores to quantify how each pattern deviates from a null model for the IDP of interest. The z-scores help in identifying putative non-random linear sequence patterns within an IDP. We demonstrate the use of NARDINI derived z-scores by identifying sequence patterns in three well-studied IDP systems. We also demonstrate how NARDINI can be deployed to study archetypal IDPs across homologs and orthologs. Overall, NARDINI is likely to aid in designing novel IDPs with a view toward engineering new sequence-function relationships or uncovering cryptic ones. We further propose that the z-scores introduced here are likely to be useful for theoretical and computational descriptions of sequence-ensemble relationships across IDPs of different compositions and lengths. (C) 2021 The Author(s). Published by Elsevier Ltd.

关键词： intrinsically disordered proteins/regions binary patterns NARDINI CIDER

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