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Journal articles on the topic 'Direction recognition'

Author: Grafiati

Published: 5 June 2025

Last updated: 16 July 2025

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1

Manish, Kumar Yadav*, Kumar Rajat, Yadav Santosh, Prajapati Ravindra, and Kshirsagar Prof. "WHEEL CHAIR USING VOICE RECOGNITION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 3 (2016): 624–28. https://doi.org/10.5281/zenodo.48327.

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The wide spread prevalence of lost limbs and sensing system is of major concern in present day due to wars, accident, age and health problems. This Omni-directional wheelchair was designed for the less able elderly to move more flexibly in narrow spaces, such as elevators or small aisle. The wheelchair is developed to help disabled patients by using speech recognition system to control the movement of wheelchair in different directions by using voice commands and also the simple movement of the patient's fingers with keypad control. From previous literature surveys it was observed that the

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OKAMOTO, MASAYOSHI, and KAZUHIKO YAMAMOTO. "ONLINE HANDWRITING CHARACTER RECOGNITION METHOD USING DIRECTIONAL AND DIRECTION-CHANGE FEATURES." International Journal of Pattern Recognition and Artificial Intelligence 13, no. 07 (1999): 1041–59. http://dx.doi.org/10.1142/s0218001499000586.

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We propose a new online recognition method to recognize handwritten cursive-style Japanese characters correctly. Our method simultaneously uses both directional features, otherwise known as offline features, and direction-change features which we designed as online features. The direction-change features express where in the mesh and in which direction the character's coordinates change. These features express both written strokes in the pen-down state and unwritten imaginary strokes in the pen-up state. The recognition rate was improved by our method over the traditional method using only dir

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3

Vuong, Quoc C., and Michael J. Tarr. "Rotation direction affects object recognition." Vision Research 44, no. 14 (2004): 1717–30. http://dx.doi.org/10.1016/j.visres.2004.02.002.

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4

Tong, Ying, and Rui Chen. "Local Dominant Directional Symmetrical Coding Patterns for Facial Expression Recognition." Computational Intelligence and Neuroscience 2019 (May 13, 2019): 1–13. http://dx.doi.org/10.1155/2019/3587036.

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To overcome the shortcomings of inaccurate textural direction representation and high-computational complexity of Local Binary Patterns (LBPs), we propose a novel feature descriptor named as Local Dominant Directional Symmetrical Coding Patterns (LDDSCPs). Inspired by the directional sensitivity of human visual system, we partition eight convolution masks into two symmetrical groups according to their directions and adopt these two groups to compute the convolution values of each pixel. Then, we encode the dominant direction information of facial expression texture by comparing each pixel’s co

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5

Kao, Fu Chien, Shin Ping R. Wang, Chih Chia Chen, Yun Kai Lin, and Chih Hsun Huang. "The Brainwave Concentration Analysis of Direction Recognition." Advanced Materials Research 950 (June 2014): 345–49. http://dx.doi.org/10.4028/www.scientific.net/amr.950.345.

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This research proposed a formula for calculating the concentration based on the view of cognitive neuroscience and a design of Brain Computer Interface (BCI) to show the strength of concentration when performing the direction recognition. The experiences proceeded by catching brainwave signals of human vision while sensing the test interfaces of graphics representing direction by brain-wave sensor and analyzed the characteristic frequency band of the brainwave related to direction recognition, then formulate the attention index of direction recognition based on the cognitive neuroscience. This

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6

Kao, Fu Chien, Shin Ping R. Wang, Chia Chun Hung, Chih Chia Chen, and Jyun Yi Du. "The Encoding Analysis of Brainwave for Direction Recognition." Applied Mechanics and Materials 284-287 (January 2013): 1661–65. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.1661.

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This research discusses about recognizing direction by brainwave characteristic frequency band in the digital coding mode. The experiences proceeded by catching brainwave signals of human vision while sensing the test interfaces of graphics and words representing direction by brainwave sensor. To compile the related samples of energies from brainwave frequency band and times of appearances, then establish the directions which stand for left-turn, right-turn, forward and backward of brainwave characteristics frequency band and its digital coding modes. Studies are to derive and analyze brainwav

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7

Fei, Lunke, Bob Zhang, Yong Xu, and Liping Yan. "Palmprint Recognition Using Neighboring Direction Indicator." IEEE Transactions on Human-Machine Systems 46, no. 6 (2016): 787–98. http://dx.doi.org/10.1109/thms.2016.2586474.

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8

Liu, Xiao Lei. "Dance Movement Recognition Based on Multimodal Environmental Monitoring Data." Journal of Environmental and Public Health 2022 (July 19, 2022): 1–8. http://dx.doi.org/10.1155/2022/1568930.

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Fine motion recognition is a challenging topic in computer vision, and it has been a trendy research direction in recent years. This study combines motion recognition technology with dance movements and the problems such as the high complexity of dance movements and fully considers the human body’s self-occlusion. The excellent motion recognition content in the dance field was studied and analyzed. A compelling feature extraction method was proposed for the dance video dataset, segmented video, and accumulated edge feature operation. By extracting directional gradient histogram features, a set

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9

Li, Min, Huabin Wang, Leqian Li, Dailei Zhang, and Liang Tao. "Finger Vein Recognition Based on a Histogram of Competitive Gabor Directional Binary Statistics." Journal of Database Management 34, no. 3 (2023): 1–19. http://dx.doi.org/10.4018/jdm.321547.

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Traditional methods of extracting finger vein texture changes and orientation features are susceptible to illumination, translation, noise, and rotation, and the process has difficulty directly extracting structural features through the original image. In this paper, the histogram of competitive Gabor directional binary statistics (HCGDBS) is proposed to extract discriminative structural features. First, the index of the largest filter value is obtained based on the multidirectional Gabor filter as the dominant direction, thereby obtaining the rotation-invariance feature. Second, according to

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10

Kota, Haripal Reddy, Vippalapally Balaji, Merugu Naveen, K. Vijay Kumar, Eerla Prashanth Kumar, and Pallam Venkatapathi. "An Affordable Optical Sensor for Safe Touchless Palm Print Biometry Detection." International Journal for Research in Applied Science and Engineering Technology 12, no. 12 (2024): 669–74. https://doi.org/10.22214/ijraset.2024.65777.

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Abstract: Palm print recognition techniques have made extensive and successful use of palm print direction patterns. In order to obtain authentic line responses in the palm print image, the majority of current direction-based techniques uses pre-defined filters, which necessitate extensive prior knowledge and typically overlooks crucial direction information. Furthermore, some noise-influenced line replies will reduce the accuracy of recognition. Another challenge for enhancing recognition performance is figuring out how to extract the discriminative elements that will make the palm print easi

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11

Wang, Zhuhe, Nan Li, Tao Wu, Haoxuan Zhang, and Tao Feng. "Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network." Journal of Intelligent Systems 30, no. 1 (2020): 209–23. http://dx.doi.org/10.1515/jisys-2019-0250.

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Abstract In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. Theoretically, the two microphones cannot distinguish the front and rear directions. H

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12

Satyendra, Rajput, and Joyti Bharti Dr. "A FACE RECOGNITION USING LINEAR-DIAGONAL BINARY GRAPH PATTERN FEATURE EXTRACTION METHOD." International Journal on Foundations of Computer Science & Technology (IJFCST) 6, no. 2 (2023): 11. https://doi.org/10.5281/zenodo.7649286.

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Face recognition is one the most interesting topic in the field in computer vision and image processing. Face recognition is a processing system that recognizes and identifies individuals human by their faces. Automatic face recognition is powerful way to provide, authorized access to control their system. Face recognition has many challenging problems (like face pose, face expression variation, illumination variation, face orientation and noise) in the field of image analysis and computer vision. This method is work on feature extraction part of face recognition. New way to extract face featu

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Okamoto, Masayoshi, and Kazuhiko Yamamoto. "On-line Handwriting Character Recognition using Directional Features and Direction-Change Features." IEEJ Transactions on Electronics, Information and Systems 119, no. 3 (1999): 358–66. http://dx.doi.org/10.1541/ieejeiss1987.119.3_358.

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14

Kim, Jong-Doo. "Improvement Direction and Recognition of Gapjil Act." Journal of the Korea Entertainment Industry Association 12, no. 4 (2018): 283–94. http://dx.doi.org/10.21184/jkeia.2018.6.12.4.283.

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15

Jia, Wei, Bob Zhang, Jingting Lu, et al. "Palmprint Recognition Based on Complete Direction Representation." IEEE Transactions on Image Processing 26, no. 9 (2017): 4483–98. http://dx.doi.org/10.1109/tip.2017.2705424.

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16

Hsia, Shih-Chang, Szu-Hong Wang, Bo-Yung Wang, and Chuan-Yu Chang. "Intelligent Surrounding Recognition for Robot Direction Control." IEEE Access 8 (2020): 200275–82. http://dx.doi.org/10.1109/access.2020.3035617.

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17

Mese, Michihiro, Hiroshi Sako, Takafumi Miyatake, Masakazu Ejiri, and Hirotada Ueda. "Direction-invariant methodology for bill pattern recognition." Systems and Computers in Japan 27, no. 8 (1996): 93–106. http://dx.doi.org/10.1002/scj.4690270808.

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18

Surekha, P., P. Vidya Sagar, and G. Ramesh. "Edge aware directional coding (EADC) for face expression recognition." Journal of Information and Optimization Sciences 46, no. 4-A (2025): 979–89. https://doi.org/10.47974/jios-1884.

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Face Expression Recognition (FER) has immense popularity in research community due to its widespread applicability in different applications. However, the currently available expression descriptors are suffering from several problems like noises, distortions and weak edges. To sort out these issues, this paper proposes an Edge Aware Directional Coding (EADC) that efficiently encodes the prominent expression related features. Initially, EADC finds out the gradients based on Kirsch Compass Mask in eight directions. Then EADC encode each pixel in facial image based on the Gradient Support of its

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19

Wu, Hao Ying, and Kai Fan. "Online Direction Classification and Recognition Using an Intuitive Tactile Communication." Applied Mechanics and Materials 543-547 (March 2014): 1542–45. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1542.

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This paper proposed an online direction classifying method for constructing an intuitive tactile communication during human-robot cooperation. The proposed approach abstracts a suitable feature set from a tactile array sensor equipped on a hand-bar. This lower computation feature extraction method analyze the weighting values concerned with oriental information from principle component analysis (PCA), together with support vector machines (SVM) classifier for direction classification and recognition. Experimental results showed an average accuracy of 96.3% and a low costs of 512μs with respect

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20

ROSSEL, SAMUEL. "Binocular Spatial Localization in the Praying Mantis." Journal of Experimental Biology 120, no. 1 (1986): 265–81. http://dx.doi.org/10.1242/jeb.120.1.265.

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The way in which mantids localize the direction and the distance of their prey has been analysed, to clarify the importance of binocular interactions. The results suggest the following major points: 1. Binocular interactions coordinate monocular directional information, such that the direction in which a mantid fixates its prey is intermediate between the image directions in the two eyes (Figs 3, 4). 2. Binocular interactions elaborate the disparity between the monocular images, thus providing the mantid with a means of estimating the distance of its prey (Fig. 5; Tables 1, 2). The above findi

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21

Wenbo Huang, First A., Second B. Changyuan Wang, and Third C. Hongbo Jia. "Ergonomics analysis based on intention inference." Journal of Intelligent & Fuzzy Systems 41, no. 1 (2021): 1281–96. http://dx.doi.org/10.3233/jifs-210191.

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Traditional intention inference methods rely solely on EEG, eye movement or tactile feedback, and the recognition rate is low. To improve the accuracy of a pilot’s intention recognition, a human-computer interaction intention inference method is proposed in this paper with the fusion of EEG, eye movement and tactile feedback. Firstly, EEG signals are collected near the frontal lobe of the human brain to extract features, which includes eight channels, i.e., AF7, F7, FT7, T7, AF8, F8, FT8, and T8. Secondly, the signal datas are preprocessed by baseline removal, normalization, and least-squares

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22

Madan, J., P. V. M. Rao, and T. K. Kundra. "Die-Casting Feature Recognition for Automated Parting Direction and Parting Line Determination." Journal of Computing and Information Science in Engineering 7, no. 3 (2006): 236–48. http://dx.doi.org/10.1115/1.2768369.

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Determining parting direction and parting line for die-cast parts is a nontrivial task that not only depends upon shape and topology of the part, but also on many process related factors. Normally, a die-casting expert decides parting direction and parting line, intuitively taking into account a large number of factors, and this process can be time consuming and cumbersome in many cases. This study addresses automated determination of parting direction and parting line for a die-cast part from part CAD model. The proposed methodology takes STEP file of the part as input for extracting die-cast

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23

Tan, Linglong, Huanyun Chen, Xiaoyao Yin, and Shiqi Zheng. "Research on Fingerprint Recognition Algorithm." Journal of Physics: Conference Series 2246, no. 1 (2022): 012069. http://dx.doi.org/10.1088/1742-6596/2246/1/012069.

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Abstract Fingerprint characteristics will not change due to growth or aging, and are unique and suitable for the field of identification. The fingerprint image is scanned from left to right and from top to bottom in order to scan the points on the entire image, and then the points on the image are judged to achieve fingerprint feature point extraction. Then, the fingerprint image is preprocessed and feature extracted, and the center point of the fingerprint, the direction field of the fingerprint image and the coordinates of the feature point are obtained. The reference direction of the finger

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24

MILLY, MIRON. "Recognition of direction of incremental sensor shaft rotation." International Journal of Electronics 68, no. 3 (1990): 471–81. http://dx.doi.org/10.1080/00207219008921190.

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25

Dominguez-Sanchez, Alex, Miguel Cazorla, and Sergio Orts-Escolano. "Pedestrian Movement Direction Recognition Using Convolutional Neural Networks." IEEE Transactions on Intelligent Transportation Systems 18, no. 12 (2017): 3540–48. http://dx.doi.org/10.1109/tits.2017.2726140.

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26

Conty, Laurence, Julie Grèzes, and David Sander. "How does perceiving eye direction modulate emotion recognition?" Behavioral and Brain Sciences 33, no. 6 (2010): 443–44. http://dx.doi.org/10.1017/s0140525x10001305.

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AbstractNiedenthal et al. postulate that eye contact with the expresser of an emotion automatically initiates embodied simulation. Our commentary explores the generality of such an eye contact effect for emotions other than happiness. Based on the appraisal theory of emotion, we propose that embodied simulation may be reinforced by mutual or averted gaze as a function of emotional context.

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27

Wu, Haoying, Hongbin Liu, and Dikai Liu. "Two-Dimensional Direction Recognition Using Uniaxial Tactile Arrays." IEEE Sensors Journal 13, no. 12 (2013): 4897–903. http://dx.doi.org/10.1109/jsen.2013.2277736.

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28

周, 谋昭. "Face Direction Recognition Based on BP Neural Network." Computer Science and Application 07, no. 02 (2017): 157–64. http://dx.doi.org/10.12677/csa.2017.72020.

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Liu, Jun, Xiaojun Jing, Zifeng Lian, and Songlin Sun. "Local Gabor Dominant Direction Pattern for Face Recognition." Chinese Journal of Electronics 24, no. 2 (2015): 245–50. http://dx.doi.org/10.1049/cje.2015.04.004.

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30

XU, YUANYUAN, BIN KONG, HU WEI, and QIANG TIAN. "LANE-BASED DIRECTION MARKING RECOGNITION USING HU MOMENTS." International Journal of Information Acquisition 09, no. 03n04 (2013): 1350016. http://dx.doi.org/10.1142/s0219878913500162.

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In intelligent vehicle system, it is significant to detect and identify road markings for vehicles to follow traffic regulation. This paper proposes a method to recognize direction markings on road surface, which is on the basis of detected lanes and uses Hu moments. First of all, the detection of lanes is based on horizontal luminance difference, which converts the RGB color image to the luminance image, calculates the horizontal luminance difference, obtains the candidate points of lanes' edge and uses least square method to fit the lanes. Secondly, with the detected lines as guide for the s

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Sun, Junhua, Lewei Huang, and Jie Zhang. "Automatic Twining Direction Recognition of Lockwire on Engine." IEEE Access 7 (2019): 155530–39. http://dx.doi.org/10.1109/access.2019.2948876.

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32

Crocket, Alastair. "Recognition, Regulation, Registration." New Zealand Journal of Counselling 34, no. 1 (2014): 53–68. http://dx.doi.org/10.24135/nzjc.v34i1.181.

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More than a decade after the passage of the Health Practitioners Competence Assurance Act 2003 it is undecided whether counselling will become a stateregulated profession. This article focuses on three directions potentially available to NZAC and its members: state regulation; the current status quo as a selfmanaging organisation; or self-regulation with a measure of state approval. It argues that counsellors need to be pragmatic in deciding which to support, since government policy considerations will influence the success of any direction we choose to take. [ABSTRACT FROM AUTHOR] Copyright o

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33

Yoo, Han-Chul, and Chang-Min Lee. "A Study on the recognition direction of Taekwondo Performance Directing Using Big Data Analysis." World Society of Taekwondo Culture 15, no. 2 (2024): 49–66. http://dx.doi.org/10.18789/jwstc.2024.43.49.

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34

Sun, Ya Jie, Yong Hong Zhang, and Shen Fang Yuan. "Screw Loosening Monitoring in UAV Wing Box Based on Phased Array Theory." Applied Mechanics and Materials 303-306 (February 2013): 533–37. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.533.

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Phased array theory was utilized in the unmanned aerial vehicle (UAV) wing box to identify the screw loosening in the structure. Phased array theory could well control the beam steering of Lamb wave to the desired directions to scan the structure for damage recognition. The time delay in special direction was calculated for the beam steering of the signal. The recognition result was shown on a mapped image.

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Xu, Xue Yan, Jiao Yu Liu, Yuan Shi, and Tuo Deng. "Face Recognition Based on Gabor Filter and Improved Linear Local Tangent Space Alignment Algorithm." Advanced Materials Research 989-994 (July 2014): 4091–94. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4091.

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In this paper, Gabor filtering and linear local tangent space alignment algorithm and its improved algorithm are used on face recognition. The Gabor wavelet transform can detect the image information in different directions and scales, according to its selective direction and frequency characteristics. The LLTSA reduces the dimension of the sample while the LLTSA and the other improved algorithms extract secondary feature. Experiment and analyze the average recognition rate of the LLTSA and its improved algorithms with the variation of dimension. The experiment results show the effectiveness o

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Feng, Yinnian, Kristine N. Brazin, Eiji Kobayashi, Robert J. Mallis, Ellis L. Reinherz та Matthew J. Lang. "Mechanosensing drives acuity of αβ T-cell recognition". Proceedings of the National Academy of Sciences 114, № 39 (2017): E8204—E8213. http://dx.doi.org/10.1073/pnas.1703559114.

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T lymphocytes use surface αβ T-cell receptors (TCRs) to recognize peptides bound to MHC molecules (pMHCs) on antigen-presenting cells (APCs). How the exquisite specificity of high-avidity T cells is achieved is unknown but essential, given the paucity of foreign pMHC ligands relative to the ubiquitous self-pMHC array on an APC. Using optical traps, we determine physicochemical triggering thresholds based on load and force direction. Strikingly, chemical thresholds in the absence of external load require orders of magnitude higher pMHC numbers than observed physiologically. In contrast, force a

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37

Hietamäki, Minna. "Attitudes and Ecumenical Recognition. How Do Attitudes Define, Facilitate, or Inhibit Ecumenical Advancement?" Exchange 51, no. 1 (2022): 61–81. http://dx.doi.org/10.1163/1572543x-20221619.

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Abstract Ecumenical texts cultivate a rich language of attitudes referring to trust, commitment, love, faithfulness, openness, etc., but their role in ecumenical advancement has been taken for granted. This article discusses attitudes in ecumenical advancement by focusing on ecumenical recognition. Some recognition theories hold attitudes, specifically personifying attitudes, to be a precondition for recognition. Contemporary recognition theories offer a rich analysis of attitudes concerning subjects and objects of recognition, the direction, and the consequences of recognition. Based on an ov

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38

Huynh, Loc Huu, Hai Quoc Luu, and Vu Duc Anh Dinh. "MODIFIED DIRECTION FEATURE AND NEURAL NETWORK BASED TECHNIQUE FOR HANDWRITING CHARACTER RECOGNITION." Science and Technology Development Journal 14, no. 2 (2011): 62–70. http://dx.doi.org/10.32508/stdj.v14i2.1910.

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Handwriting character recognition is an important research topic which has various applications in surveillance, radar, robot technology... In this paper, we propose the implementation of the handwriting character recognition using off-line handwriting recognition. The approach consists of two steps: to make thin handwriting by keeping the skeleton of character and reject redundant points caused by humam’s stroke width and to modify direction method which provide high accuracy and simply structure analysis method to extract character’s features from its skeleton. In addition, we build neural n

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Shin, Byung-Gon, and Yong-Hwan Cho. "Recognition of Gesture Characters Using Direction and Duration Time." Joural of the Korea Entertainment Industry Association 1, no. 1 (2007): 66. http://dx.doi.org/10.21184/jkeia.2007.12.1.1.66.

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Heng Liu, Caihong Zhang, and Jinggang Lv. "A Fast and Robust Hand Waving Direction Recognition Scheme." Journal of Convergence Information Technology 7, no. 15 (2012): 46–53. http://dx.doi.org/10.4156/jcit.vol7.issue15.6.

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Suwabe, Miki, Naohiko Hanajima, Hiromitsu Hikita, and Mitsuhisa Yamashita. "418 Recognition of the direction of face using features." Proceedings of Conference of Hokkaido Branch 2005.44 (2005): 152–53. http://dx.doi.org/10.1299/jsmehokkaido.2005.44.152.

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Florea, Laura, Corneliu Florea, and Constantin Vertan. "Recognition of the gaze direction: Anchoring with the eyebrows." Journal of Visual Communication and Image Representation 35 (February 2016): 67–77. http://dx.doi.org/10.1016/j.jvcir.2015.12.003.

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Jung, Do-Joon, and Jeong-Oh Yoon. "Human Activity Recognition using Model-based Gaze Direction Estimation." Journal of the Korea Industrial Information Systems Research 16, no. 4 (2011): 9–18. http://dx.doi.org/10.9723/jksiis.2011.16.4.009.

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44

Cheng, Y., C. L. Wang, Z. Y. Li, Y. K. Hou, and C. X. Zhao. "Multiscale principal contour direction for varying lighting face recognition." Electronics Letters 46, no. 10 (2010): 680. http://dx.doi.org/10.1049/el.2010.0696.

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Fei, Lunke, Bob Zhang, Wei Zhang, and Shaohua Teng. "Local apparent and latent direction extraction for palmprint recognition." Information Sciences 473 (January 2019): 59–72. http://dx.doi.org/10.1016/j.ins.2018.09.032.

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46

Baloola, Mohamed Osman, Fatimah Ibrahim, and Mas S. Mohktar. "Optimization of Medication Delivery Drone with IoT-Guidance Landing System Based on Direction and Intensity of Light." Sensors 22, no. 11 (2022): 4272. http://dx.doi.org/10.3390/s22114272.

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This paper presents an optimization of the medication delivery drone with the Internet of Things (IoT)-Guidance Landing System based on direction and intensity of light. The IoT-GLS was incorporated into the system to assist the drone’s operator or autonomous system to select the best landing angles for landing. The landing selection was based on the direction and intensity of the light. The medication delivery drone system was developed using an Arduino Uno microcontroller board, ESP32 DevKitC V4 board, multiple sensors, and IoT mobile apps to optimize face detection. This system can detect a

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Duan, Qingqing. "Video action recognition: A survey." Applied and Computational Engineering 6, no. 1 (2023): 1374–86. http://dx.doi.org/10.54254/2755-2721/6/20230806.

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In recent years, as computer vision technology advances quickly, video action recognition has become a research hotspot. However, the field of video action recognition still faces many problems and challenges, such as the complex temporal dynamics of video data and the high computation cost caused by the explosive growth of video data. This paper summarizes the algorithms of video action recognition, and introduces them in two parts, namely, traditional handcrafted representation methods and deep learning representation methods. Among them, the traditional handcrafted representation methods ar

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Kyi, Pyar Zaw, and Mar Kyu Zin. "Myanmar Warning Board Recognition System." International Journal of Research and Engineering 5, no. 8 (2018): 480–85. https://doi.org/10.21276/ijre.2018.5.8.3.

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In any country, warning text is described on the signboards or wallpapers to follow by everybody. This paper present Myanmar character recognition from various warning text signboards using block based pixel count and eight-directions chain code. Character recognition is the process of converting a printed or typewritten or handwritten text image file into editable and searchable text file. In this system, the characters on the warning signboard images are recognized using the hybrid eight direction chain code features and 16-blocks based pixel count features. Basically, there are three steps

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Hong, Duan, and Yang Luo. "A Gesture Trace Detection Method Using DTW." Applied Mechanics and Materials 380-384 (August 2013): 3874–77. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3874.

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This paper puts forward a gestures trajectory recognition method based on DTW. Through the direction characteristic to calculate trajectory characteristics, and through the coding to quantize direction characteristic, and at the same time, considering the direction of the cyclical, proposed a new distance equation for calculating distance. The experimental results prove that the method realized the dynamic gesture recognition in the complex static background.

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Chaudhuri, Shomesh E., Faisal Karmali, and Daniel M. Merfeld. "Whole body motion-detection tasks can yield much lower thresholds than direction-recognition tasks: implications for the role of vibration." Journal of Neurophysiology 110, no. 12 (2013): 2764–72. http://dx.doi.org/10.1152/jn.00091.2013.

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Earlier spatial orientation studies used both motion-detection (e.g., did I move?) and direction-recognition (e.g., did I move left/right?) paradigms. The purpose of our study was to compare thresholds measured with motion-detection and direction-recognition tasks on a standard Moog motion platform to see whether a substantial fraction of the reported threshold variation might be explained by the use of different discrimination tasks in the presence of vibrations that vary with motion. Thresholds for the perception of yaw rotation about an earth-vertical axis and for interaural translation in

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