Search results for: hand written character recognition

Authors: Van Nhan Nguyen, Harald Holone

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Over the past few years, a lot of research has been conducted to bring Automatic Speech Recognition (ASR) into various areas of Air Traffic Control (ATC), such as air traffic control simulation and training, monitoring live operators for with the aim of safety improvements, air traffic controller workload measurement and conducting analysis on large quantities controller-pilot speech. Due to the high accuracy requirements of the ATC context and its unique challenges, automatic speech recognition has not been widely adopted in this field. With the aim of providing a good starting point for researchers who are interested bringing automatic speech recognition into ATC, this paper gives an overview of possibilities and challenges of applying automatic speech recognition in air traffic control. To provide this overview, we present an updated literature review of speech recognition technologies in general, as well as specific approaches relevant to the ATC context. Based on this literature review, criteria for selecting speech recognition approaches for the ATC domain are presented, and remaining challenges and possible solutions are discussed.

Keywords: automatic speech recognition, asr, air traffic control, atc

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Authors: E. Calil, L. A. Pereira

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The acquisition of orthography is a complex process, involving both lexical and grammatical questions. This learning occurs simultaneously with the domain of multiple textual aspects (e.g.: graphs, punctuation, etc.). However, most of the research on orthographic acquisition focus on this acquisition from an autonomous point of view, separated from the process of textual production. This means that their object of analysis is the production of words selected by the researcher or the requested sentences in an experimental and controlled setting. In addition, the analysis of the Spelling Problems (SP) are identified by the researcher on the sheet of paper. Considering the perspective of Textual Genetics, from an enunciative approach, this study will discuss the SPs recognized by dyads of newly literate students, while they are writing a text collaboratively. Six proposals of textual production were registered, requested by a 2nd year teacher of a Portuguese Primary School between January and March 2015. In our case study we discuss the SPs recognized by the dyad B and L (7 years old). We adopted as a methodological tool the Ramos System audiovisual record. This system allows real-time capture of the text in process and of the face-to-face dialogue between both students and their teacher, and also captures the body movements and facial expressions of the participants during textual production proposals in the classroom. In these ecological conditions of multimodal registration of collaborative writing, we could identify the emergence of SP in two dimensions: i. In the product (finished text): SP identification without recursive graphic marks (without erasures) and the identification of SPs with erasures, indicating the recognition of SP by the student; ii. In the process (text in progress): identification of comments made by students about recognized SPs. Given this, we’ve analyzed the comments on identified SPs during the text in progress. These comments characterize a type of reformulation referred to as Commented Oral Erasure (COE). The COE has two enunciative forms: Simple Comment (SC) such as ' 'X' is written with 'Y' '; or Unfolded Comment (UC), such as ' 'X' is written with 'Y' because...'. The spelling COE may also occur before or during the SP (Early Spelling Recognition - ESR) or after the SP has been entered (Later Spelling Recognition - LSR). There were 631 words entered in the 6 stories written by the B-L dyad, 145 of them containing some type of SP. During the text in progress, the students recognized orally 174 SP, 46 of which were identified in advance (ESRs) and 128 were identified later (LSPs). If we consider that the 88 erasure SPs in the product indicate some form of SP recognition, we can observe that there were twice as many SPs recognized orally. The ESR was characterized by SC when students asked their colleague or teacher how to spell a given word. The LSR presented predominantly UC, verbalizing meta-orthographic arguments, mostly made by L. These results indicate that writing in dyad is an important didactic strategy for the promotion of metalinguistic reflection, favoring the learning of spelling.

Keywords: collaborative writing, erasure, learning, metalinguistic awareness, spelling, text production

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Authors: Malika Yaici, Soraya Aloui, Sara Semchaoui

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This paper deals with human activity recognition from sensor data. It is an active research area, and the main objective is to obtain a high recognition rate. In this work, a recognition system based on expert systems is proposed; the recognition is performed using the objects, object states, and gestures and taking into account the context (the location of the objects and of the person performing the activity, the duration of the elementary actions and the activity). The system recognizes complex activities after decomposing them into simple, easy-to-recognize activities. The proposed method can be applied to any type of activity. The simulation results show the robustness of our system and its speed of decision.

Keywords: human activity recognition, ubiquitous computing, context-awareness, expert system

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: Aniket S. Joshi, Aditya R. Mane, Arjun Tukaram

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In the 21st century, in the era of e-world, people are continuously getting updated by daily information such as weather conditions, news, stock exchange market updates, new projects, cricket updates, sports and other such applications. In the busy situation, they want this information on the little use of keyboard, time. Today in order to get such information user have to repeat same mouse and keyboard actions which includes time and inconvenience. In India due to rural background many people are not much familiar about the use of computer and internet also. Also in small clinics, small offices, and hotels and in the airport there should be a system which retrieves daily information with the minimum use of keyboard and mouse actions. We plan to design application based project that can easily retrieve information with minimum use of keyboard and mouse actions and make our task more convenient and easier. This can be possible with an image processing application which takes real time hand gestures which will get matched by system and retrieve information. Once selected the functions with hand gestures, the system will report action information to user. In this project we use real time hand gesture movements to select required option which is stored on the screen in the form of RSS Feeds. Gesture will select the required option and the information will be popped and we got the information. A real time hand gesture makes the application handier and easier to use.

Keywords: hand detection, hand tracking, hand gesture recognition, HSV color model, Blob detection

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Authors: Malika Yaici, Soraya Aloui, Sara Semchaoui

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Recognition of human activities from sensor data is an active research area, and the main objective is to obtain a high recognition rate. In this work, we propose a recognition system based on expert systems. The proposed system makes the recognition based on the objects, object states, and gestures, taking into account the context (the location of the objects and of the person performing the activity, the duration of the elementary actions, and the activity). This work focuses on complex activities which are decomposed into simple easy to recognize activities. The proposed method can be applied to any type of activity. The simulation results show the robustness of our system and its speed of decision.

Keywords: human activity recognition, ubiquitous computing, context-awareness, expert system

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Authors: Mohammad Hossain Mohammadi, Saif Al Ameri, Sana Ziaei, Jinane Mounsef

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Automated enumeration of the number of hand fingers is widely used in several motion gaming and distance control applications, and is discussed in several published papers as a starting block for hand recognition systems. The automated finger enumeration technique should not only be accurate, but also must have a fast response for a moving-picture input. The high performance of video in motion games or distance control will inhibit the program’s overall speed, for image processing software such as Matlab need to produce results at high computation speeds. Since an automated finger enumeration with minimum error and processing time is desired, a comparative study between two finger enumeration techniques is presented and analyzed in this paper. In the pre-processing stage, various image processing functions were applied on a real-time video input to obtain the final cleaned auto-cropped image of the hand to be used for the two techniques. The first technique uses the known morphological tool of skeletonization to count the number of skeleton’s endpoints for fingers. The second technique uses a radial distance method to enumerate the number of fingers in order to obtain a one dimensional hand representation. For both discussed methods, the different steps of the algorithms are explained. Then, a comparative study analyzes the accuracy and speed of both techniques. Through experimental testing in different background conditions, it was observed that the radial distance method was more accurate and responsive to a real-time video input compared to the skeletonization method. All test results were generated in Matlab and were based on displaying a human hand for three different orientations on top of a plain color background. Finally, the limitations surrounding the enumeration techniques are presented.

Keywords: comparative study, hand recognition, fingertip detection, skeletonization, radial distance, Matlab

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Authors: Ulil Afidah, Muhamad Fathan Mubin, Firdha Aulia

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Code riverbanks Yogyakarta is a settlement area with middle to lower social classes. Socio-economic situation is affecting the behavior of society. This research aimed to find and explain the implementation and the assessment of character education which were done in elementary schools in Code riverside, Yogyakarta region of Indonesia. This research is a qualitative research which the subjects were the kids of Code riverbanks, Yogyakarta. The data were collected through interviews and document studies and analyzed qualitatively using the technique of interactive analysis model of Miles and Huberman. The results show that: (1) The learning process of character education was done by integrating all aspects such as democratic and interactive learning session also introducing role model to the students. 2) The assessment of character education was done by teacher based on teaching and learning process and an activity in outside the classroom that was the criterion on three aspects: Cognitive, affective and psychomotor.

Keywords: character, Code riverbanks, education, Yogyakarta

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Authors: Mariya Dzhyoyeva

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In the present paper, I examine manifestations of toxic masculinity in the novels by Tomás Eloy Martínez, a post-Boom author, journalist, literary critic, and one of the representatives of the Argentine writing diaspora. I focus on the analysis of Martínez´s characters that display hypermasculine traits to define the relationship between toxic masculinity and power, including the power of authorship and violence as they are represented in his novels. The analysis reveals a complex network in which gender, power, and violence are intertwined and influence and modify each other. As the author exposes toxic masculine behaviors that generate violence, he looks to undermine them. Departing from M. Kimmel´s idea of masculinity as homophobia, I examine how Martínez “outs” his characters by incorporating into the narrative some secret, privileged sources that provide alternative accounts of their otherwise hypermasculine lives. These background stories expose their “weaknesses,” both physical and mental, and thereby feminize them in their own eyes. In a similar way, the toxic masculinity of the fictional male author that wields his power by abusing the written word as he abuses the female character in the story is exposed as a complex of insecurities accumulated by the character due to his childhood trauma. The artistic technique that Martínez uses to condemn the authoritarian male behavior is accessing his subjectivity and subverting it through a multiplicity of identities. Martínez takes over the character’s “I” and turns it into a host of pronouns with a constantly shifting point of reference that distorts not only the notions of gender but also the very notion of identity. In doing so, he takes the character´s affirmation of masculinity to the limit where the very idea of it becomes unsustainable. Viewed in the context of Martínez´s own exilic story, the condemnation of toxic masculine power turns into the condemnation of dictatorship and authoritarianism.

Keywords: gender, masculinity., toxic masculinity, authoritarian, Argentine literature, Martínez

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Authors: Shynn Lim, Ching Tan

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The paper presents the PASSION Programme designed by a government school in Singapore, guided by national goals as well as research-based pedagogies that aims to nurture students to become lifelong learners with the strength of character. The design and enactment of the integrated approach to develop in students good character, resilience and social-emotional well-being, future readiness, and active citizenship is guided by a set of principles that amalgamates Biesta’s domains of purposes of education and authentic learning. Data in terms of evidence of students’ learning and students’ feedback were collected, analysed, and suggests that the learning experience benefitted students by boosting their self-confidence, self-directed and collaborative learning skills, as well as empathy.

Keywords: lifelong learning, character and citizenship education, education and career guidance, 21CC, teaching and learning empathy

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Authors: Seo-Hee Kim, Kee-Won Kim, Seung-Hoon Kim

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The most important elements of a novel are the characters, events and background. The background represents the time, place and situation that character appears, and conveys event and atmosphere more realistically. If readers have the proper knowledge about background of novels, it may be helpful for understanding the atmosphere of a novel and choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels because spatio-temporal background especially performs an important role in historical novels among the genre of Korean novels. To the best of our knowledge, we could not find previous study that was aimed at Korean novels. In this paper, we build a Korean historical national dictionary. Our dictionary has historical places and temple names of kings over many generations as well as currently existing spatial words or temporal words in Korean history. We also present a method for recognizing spatio-temporal background based on patterns of phrasal words in Korean sentences. Our rules utilize postposition for spatial background recognition and temple names for temporal background recognition. The knowledge of the recognized background can help readers to understand the flow of events and atmosphere, and can use to visualize the elements of novels.

Keywords: data mining, Korean historical novels, Korean linguistic feature, spatio-temporal background

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Authors: Rania Ahmed Kadry Abdel Gawad Birry, Mohamed El-Habrouk

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This paper presents a brief survey of the techniques used for sign language recognition along with the types of sensors used to perform the task. It presents a modified method for identification of an isolated sign language gesture using Microsoft Kinect with the OpenNI framework. It presents the way of extracting robust features from the depth image provided by Microsoft Kinect and the OpenNI interface and to use them in creating a robust and accurate gesture recognition system, for the purpose of ASL translation. The Prime Sense’s Natural Interaction Technology for End-user - NITE™ - was also used in the C++ implementation of the system. The algorithm presents a simple finger counting algorithm for static signs as well as directional Finite State Machine (FSM) description of the hand motion in order to help in translating a sign language gesture. This includes both letters and numbers performed by a user, which in-turn may be used as an input for voice pronunciation systems.

Keywords: American sign language, finger counting, hand tracking, Microsoft Kinect

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Authors: Sevil Igit, Merve Meric, Sarp Erturk

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In this paper, it is proposed to improve Daisy descriptor based face recognition using a novel One-Bit Transform (1BT) based pre-registration approach. The 1BT based pre-registration procedure is fast and has low computational complexity. It is shown that the face recognition accuracy is improved with the proposed approach. The proposed approach can facilitate highly accurate face recognition using DAISY descriptor with simple matching and thereby facilitate a low-complexity approach.

Keywords: face recognition, Daisy descriptor, One-Bit Transform, image registration

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Authors: P. Revathi, T. Mrunalini, K. Padma Priya, P. Ramya, R. Saranya

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During the tough times of covid, those people who were hospitalized found it difficult to always convey what they wanted to or needed to the attendee. Sometimes the attendees might also not be there. In that case, the patients can use simple hand gestures to control electrical appliances (like its set it for a zero watts bulb)and three other gestures for voice note intimation. In this AI-based hand recognition project, NodeMCU is used for the control action of the relay, and it is connected to the firebase for storing the value in the cloud and is interfaced with the python code via raspberry pi. For three hand gestures, a voice clip is added for intimation to the attendee. This is done with the help of Google’s text to speech and the inbuilt audio file option in the raspberry pi 4. All the 5 gestures will be detected when shown with their hands via a webcam which is placed for gesture detection. A personal computer is used for displaying the gestures and for running the code in the raspberry pi imager.

Keywords: onion harvesting, automatic pluging, camera, raspberry pi

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Authors: Agus Masrukhin

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This research aims to find and analyze the model of character building in the Police Headquarters in Bali with a case study of Muslim members in improving the quality of the morality of its members. The formation of patterns of thinking, behavior, mentality, and police officers noble character, later can be used as a solution to reduce the hedonistic nature of the challenges in the era of globalization. The benefit of this study is expected to be a positive recommendation to find a constructive character building models of police officers in the Republic of Indonesia, especially Bali Police. For the long term, the discovery of the character building models can be developed for the entire police force in Indonesia. The type of research that would apply in this study researchers mix the qualitative research methods based on the narrative between the subject and the concrete experience of field research and quantitative research methods with 92 respondents from the police regional police Bali. This research used a descriptive analysis and SWOT analysis then it is presented in the FGD (focus group discussion). The results of this research indicate that the variable modeling the leadership of the police and variable police offices culture have significant influence on the implementation of spiritual development.

Keywords: positive constructive, hedonistic, character models, morality

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Y. Y. Pang, N. A. Ismail

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The map is a powerful and convenient tool in helping us to navigate to different places, but the use of indirect devices often makes its usage cumbersome. This study intends to propose a new map navigation dialogue that uses hand gesture. A set of dialogue was developed from users’ perspective to provide users complete freedom for panning, zooming, rotate, and find direction operations. A participatory design experiment was involved here where one hand gesture and two hand gesture dialogues had been analysed in the forms of hand gestures to develop a set of usable dialogues. The major finding was that users prefer one-hand gesture compared to two-hand gesture in map navigation.

Keywords: hand gesture, map navigation, participatory design, intuitive interaction

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Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

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Authors: Cecilia Amponsem-Boateng, Timothy B. Oppong, Haiyan Yang, Guangcai Duan

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The human palm has been identified as one of the richest habitats for human microbial accommodation making hand hygiene essential to primary prevention of infection. Since the hand is in constant contact with fomites which have been proven to be mostly contaminated, building hand hygiene habits is essential for the prevention of infection. This research was conducted to assess the hand hygiene habits of Ghanaian youths in Accra. This study used a survey as a quantitative method of research. The findings of the study revealed that out of the 254 participants who fully answered the questionnaire, 22% had the habit of washing their hands after outings while only 51.6% had the habit of washing their hands after using the bathroom. However, about 60% of the participants said they sometimes ate with their hands while 28.9% had the habit of eating with the hand very often, a situation that put them at risk of infection from their hands since some participants had poor handwashing habits; prompting the need for continuous education on hand hygiene.

Keywords: hand hygiene, hand hygiene habit, hand washing, hand sanitizer use

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

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This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

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Authors: U. Ravi Babu, Mohd Mastan

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The present paper proposes a novel approach for handwritten digit recognition system. The present paper extract digit image features based on distance measure and derives an algorithm to classify the digit images. The distance measure can be performing on the thinned image. Thinning is the one of the preprocessing technique in image processing. The present paper mainly concentrated on an extraction of features from digit image for effective recognition of the numeral. To find the effectiveness of the proposed method tested on MNIST database, CENPARMI, CEDAR, and newly collected data. The proposed method is implemented on more than one lakh digit images and it gets good comparative recognition results. The percentage of the recognition is achieved about 97.32%.

Keywords: handwritten digit recognition, distance measure, MNIST database, image features

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Authors: Faizan Tariq, Moayid Ali Zaidi

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Facial emotion recognition algorithms are expanding rapidly now a day. People are using different algorithms with different combinations to generate best results. There are six basic emotions which are being studied in this area. Author tried to recognize the facial expressions using object detector algorithms instead of traditional algorithms. Two object detection algorithms were chosen which are Faster R-CNN and YOLO. For pre-processing we used image rotation and batch normalization. The dataset I have chosen for the experiments is Static Facial Expression in Wild (SFEW). Our approach worked well but there is still a lot of room to improve it, which will be a future direction.

Keywords: face recognition, emotion recognition, deep learning, CNN

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Authors: Marie Komorna, Katerina Hadkova

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One reason why hearing disabilities as compared to other disabilities are considered to be less serious, is the belief that deaf and hard of hearing persons can read and write without problems and can therefore fairly easily compensate for problems related to their limited ability to hear sound. However in reality this is not the case, especially as regards written Czech, deaf persons are often not able to communicate their message clearly to its recipients. Their inability to communicate fully in written language is one of the most severe problems facing a number of deaf persons, a problem which they face and which makes it difficult for them to function in a sound-based environment. Despite this fact, this issue is one which has been given only a minimum of attention in the Czech Republic. That is why we decided to focus our research on this issue, specifically targeting written communication of deaf pupils in primary and secondary schools. The paper summarizes the background and objectives of this research. The written work of deaf respondents was obtained in response to a narrative based on a series of images which depicted a continuous storyline. Based on an analysis of the obtained written work we tried to describe the specifics of the narrative abilities of the deaf authors of these texts. We also analyzed other aspects and specific traits of text written by deaf authors at a phonetic-phonological, lexical-semantic, morphological and syntactic, respectively pragmatic level. Based on the results of the project it will be possible to increase knowledge of the communication abilities of deaf persons in written Czech. The obtained data may be used during future research and for teaching purposes and/or education concepts for teaching Czech to deaf pupils.

Keywords: communication competence, deaf, narrative, written texts

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Authors: Tingting Huang, Sha Li, Geoffrey Griffiths, Martin Lukac, Jianning Zhu

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Territorial landscapes have experienced a gradual loss of their typical characteristics during long-term human activities. In order to protect the integrity of regional landscapes, it is necessary to characterize, evaluate and protect them in a graded manner. The study takes Fujian, China, as an example and classifies the landscape characters of the site at the regional scale, middle scale, and detailed scale. A multi-scale approach combining parametric and holistic approaches is used to classify and partition the landscape character types (LCTs) and landscape character areas (LCAs) at different scales, and a multi-element landscape assessment approach is adopted to explore the conservation strategies of the landscape character. Firstly, multiple fields and multiple elements of geography, nature and humanities were selected as the basis of assessment according to the scales. Secondly, the study takes a parametric approach to the classification and partitioning of landscape character, Principal Component Analysis, and two-stage cluster analysis (K-means and GMM) in MATLAB software to obtain LCTs, combines with Canny Operator Edge Detection Algorithm to obtain landscape character contours and corrects LCTs and LCAs by field survey and manual identification methods. Finally, the study adopts the Landscape Sensitivity Assessment method to perform landscape character conservation analysis and formulates five strategies for different LCAs: conservation, enhancement, restoration, creation, and combination. This multi-scale identification approach can efficiently integrate multiple types of landscape character elements, reduce the difficulty of broad-scale operations in the process of landscape character conservation, and provide a basis for landscape character conservation strategies. Based on the natural background and the restoration of regional characteristics, the results of landscape character assessment are scientific and objective and can provide a strong reference in regional and national scale territorial spatial planning.

Keywords: parameterization, multi-scale, landscape character identify, landscape character assessment

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Authors: Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi

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In this paper, we propose an improved face recognition algorithm using histogram-based features in spatial and frequency domains. For adding spatial information of the face to improve recognition performance, a region-division (RD) method is utilized. The facial area is firstly divided into several regions, then feature vectors of each facial part are generated by Binary Vector Quantization (BVQ) histogram using DCT coefficients in low frequency domains, as well as Local Binary Pattern (LBP) histogram in spatial domain. Recognition results with different regions are first obtained separately and then fused by weighted averaging. Publicly available ORL database is used for the evaluation of our proposed algorithm, which is consisted of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions. It is demonstrated that face recognition using RD method can achieve much higher recognition rate.

Keywords: binary vector quantization (BVQ), DCT coefficients, face recognition, local binary patterns (LBP)

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Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

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Authors: Tuiana A. Aiusheeva, Sergey S. Tamozhnikov, Alexander E. Saprygin, Arina A. Antonenko, Valentina V. Stepanova, Natalia N. Tolstykh, Alexander N. Savostyanov

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Situation of choice is an important condition for the formation of essential character qualities of a child, such as being initiative, responsible, hard-working. We have studied the behavioral and EEG reactions in Russian schoolchildren during recognition of syntactic errors in emotionally colored sentences that describe the choice situation. Twenty healthy children (mean age 9,0±0,3 years, 12 boys, 8 girls) were examined. Forty sentences were selected for the experiment; the half of them contained a syntactic error. The experiment additionally had the hidden condition: 50% of the sentences described the children's own choice and were emotionally colored (positive or negative). The other 50% of the sentences described the forced-choice situation, also with positive or negative coloring. EEG were recorded during execution of error-recognition task. Reaction time and quality of syntactic error detection were chosen as behavioral measures. Event-related spectral perturbation (ERSP) was applied to characterize the oscillatory brain activity of children. There were two time-frequency intervals in EEG reactions: (1) 500-800 ms in the 3-7 Hz frequency range (theta synchronization) and (2) 500-1000 ms in the 8-12 Hz range (alpha desynchronization). We found out that behavioral and brain reactions in child brain during recognition of positive and negative sentences describing forced-choice situation did not have significant differences. Theta synchronization and alpha desynchronization were stronger during recognition of sentences with children's own choice, especially with negative coloring. Also, the quality and execution time of the task were higher for this types of sentences. The results of our study will be useful for improvement of teaching methods and diagnostics of children affective disorders.

Keywords: choice situation, electroencephalogram (EEG), emotionally colored sentences, schoolchildren

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Authors: Bency Jacob, S.B. Waykar

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Degradations in historical document images appear due to aging of the documents. It is very difficult to understand and retrieve text from badly degraded documents as there is variation between the document foreground and background. Thresholding of such document images either result in broken characters or detection of false texts. Numerous algorithms exist that can separate text and background efficiently in the textual regions of the document; but portions of background are mistaken as text in areas that hardly contain any text. This paper presents a way to overcome these problems by a robust binarization technique that recovers the text from a severely degraded document images and thereby increases the accuracy of optical character recognition systems. The proposed document recovery algorithm efficiently removes degradations from document images. Here we are using the ostus method ,local thresholding and global thresholding and after the binarization training and recognizing the characters in the degraded documents.

Keywords: binarization, denoising, global thresholding, local thresholding, thresholding

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

Abstract:

Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

Procedia PDF Downloads 82

Authors: Ismahafezi Ismail, Mohd Shahrizal Sunar

Abstract:

The motion of a realistic 3D humanoid character is very important especially for the industries developing computer animations and games. However, this type of motion is seen with a very complex dimensional data as well as body position, orientation, and joint rotation. Integrated Style Motion Editor (ISME), on the other hand, is a method used to alter the 3D humanoid motion capture data utilised in computer animation and games development. Therefore, this study was carried out with the purpose of demonstrating a method that is able to manipulate and deform different motion styles by integrating Key Pose Deformation Technique and Trajectory Control Technique. This motion editing method allows the user to generate new motions from the original motion capture data using a simple interface control. Unlike the previous method, our method produces a realistic humanoid motion style in real time.

Keywords: computer animation, humanoid motion, motion capture, motion editing

Procedia PDF Downloads 355