• Title, Summary, Keyword: recognition

Search Result 18,010, Processing Time 0.064 seconds

A Research on the Measurement of Human Factor Algorithm 3D Object (3차원 영상 객체 휴먼팩터 알고리즘 측정에 관한 연구)

  • Choi, Byungkwan
    • Journal of the Korea Society of Digital Industry and Information Management
    • /
    • v.14 no.2
    • /
    • pp.35-47
    • /
    • 2018
  • The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.

Using a Multi-Faced Technique SPFACS Video Object Design Analysis of The AAM Algorithm Applies Smile Detection (다면기법 SPFACS 영상객체를 이용한 AAM 알고리즘 적용 미소검출 설계 분석)

  • Choi, Byungkwan
    • Journal of the Korea Society of Digital Industry and Information Management
    • /
    • v.11 no.3
    • /
    • pp.99-112
    • /
    • 2015
  • Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

A Study on Grapheme and Grapheme Recognition Using Connected Components Grapheme for Machine-Printed Korean Character Recognition

  • Lee, Kyong-Ho
    • Journal of the Korea Society of Computer and Information
    • /
    • v.21 no.9
    • /
    • pp.27-36
    • /
    • 2016
  • Recognition of grapheme is a very important process in the recognition within 'Hangul(Korean written language)' letters using phoneme recognition. It is because the success or failure in the recognition of phoneme greatly affects the recognition of letters. For this reason, it is reported that separation of phonemes is the biggest difficulty in the phoneme recognition study. The current study separates and suggests the new phonemes that used the connective elements that are helpful for dividing phonemes, recommends the features for recognition of such suggested phonemes, databases this, and carried out a set of experiments of recognizing phonemes using the suggested features. The current study used 350 letters in the experiment of phoneme separation and recognition. In this particular kind of letters, there were 1,125 phonemes suggested. In the phoneme separation experiment, the phonemes were divided in the rate of 100%, and the phoneme recognition experiment showed the recognition rate of 98% in recognizing only 14 phonemes into different ones.

A technology of realistic multi-media display and odor recognition using olfactory sensors (후각 센서를 이용한 냄새 인식 및 실감형 멀티미디어 표현 기술)

  • Lee, Hyeon Gu;Rho, Yong Wan
    • Journal of the Korea Society of Digital Industry and Information Management
    • /
    • v.6 no.4
    • /
    • pp.33-43
    • /
    • 2010
  • In this paper, we propose a floral scent recognition using odor sensors and a odor display using odor distribution system. Proposed odor recognition has method of correlation coefficient between sensors that select optimal sensors in floral scent recognition system of selective multi-sensors. Proposed floral scent recognition system consists of four module such as floral scent acquisition module, optimal sensor decision module, entropy-based floral scent detection module, and floral scent recognition module. Odor distribution system consists of generation module of distribution information, control module of distribution, output module of distribution. We applied to floral scent recognition for performance evaluation of proposed sensors decision method. As a result, application of proposed method with floral scent recognition obtained recognition rate of 95.67% case of using 16 sensors while applied floral scent recognition system of proposed sensor decision method confirmed recognition rate of 96% using only 8 sensors. Also, we applied to odor display of proposed method and obtained 3.18 thorough MOS experimentation.

ASM Algorithm Applid to Image Object spFACS Study on Face Recognition (영상객체 spFACS ASM 알고리즘을 적용한 얼굴인식에 관한 연구)

  • Choi, Byungkwan
    • Journal of the Korea Society of Digital Industry and Information Management
    • /
    • v.12 no.4
    • /
    • pp.1-12
    • /
    • 2016
  • Digital imaging technology has developed into a state-of-the-art IT convergence, composite industry beyond the limits of the multimedia industry, especially in the field of smart object recognition, face - Application developed various techniques have been actively studied in conjunction with the phone. Recently, face recognition technology through the object recognition technology and evolved into intelligent video detection recognition technology, image recognition technology object detection recognition process applies to skills through is applied to the IP camera, the image object recognition technology with face recognition and active research have. In this paper, we first propose the necessary technical elements of the human factor technology trends and look at the human object recognition based spFACS (Smile Progress Facial Action Coding System) for detecting smiles study plan of the image recognition technology recognizes objects. Study scheme 1). ASM algorithm. By suggesting ways to effectively evaluate psychological research skills through the image object 2). By applying the result via the face recognition object to the tooth area it is detected in accordance with the recognized facial expression recognition of a person demonstrated the effect of extracting the feature points.

The Design and Implementation of a Performance Evaluation Tool for the Face Recognition System (얼굴인식시스템 성능평가 도구의 설계 및 구현)

  • Shin, Woo-Chang
    • Journal of Information Technology Services
    • /
    • v.6 no.2
    • /
    • pp.161-175
    • /
    • 2007
  • Face recognition technology has lately attracted considerable attention because of its non-intrusiveness, usability and applicability. Related companies insist that their commercial products show the recognition rates more than 95% according to their self-testing. But, the rates cannot be admitted as official recognition rates. So, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of face recognition systems. In this paper, I propose a reference model for biometrics recognition evaluation tools, and implement an evaluation tool for the face recognition system based on the proposed reference model.

Emotion Recognition using Robust Speech Recognition System (강인한 음성 인식 시스템을 사용한 감정 인식)

  • Kim, Weon-Goo
    • Journal of Korean Institute of Intelligent Systems
    • /
    • v.18 no.5
    • /
    • pp.586-591
    • /
    • 2008
  • This paper studied the emotion recognition system combined with robust speech recognition system in order to improve the performance of emotion recognition system. For this purpose, the effect of emotional variation on the speech recognition system and robust feature parameters of speech recognition system were studied using speech database containing various emotions. Final emotion recognition is processed using the input utterance and its emotional model according to the result of speech recognition. In the experiment, robust speech recognition system is HMM based speaker independent word recognizer using RASTA mel-cepstral coefficient and its derivatives and cepstral mean subtraction(CMS) as a signal bias removal. Experimental results showed that emotion recognizer combined with speech recognition system showed better performance than emotion recognizer alone.

Parents' recognition and attitudes toward national health insurance coverage of sealant by dental hygienist (치아홈메우기의 건강보험 급여화와 치과위생사 시술에 대한 학부모의 인식 및 태도)

  • Kim, Yun-Jeong
    • Journal of Korean society of Dental Hygiene
    • /
    • v.15 no.6
    • /
    • pp.1099-1105
    • /
    • 2015
  • Objectives: The purpose of this study was to investigate parents' recognition and attitudes toward national health insurance coverage of sealant by the dental hygienists. Methods: A self-reported questionnaire was filled out by 329 elementary school children parents in G metropolitan city and N city from July 11 to 27, 2015. The questionnaire consisted of general characteristics of the subjects, recognition and attitudes toward national health insurance coverage of sealant and sealant by the dental hygienist, and recognition toward national health insurance. The data were analyzed by a descriptive analyses, multiple regression and logistic regression analysis using SPSS 12.0 program. Results: Recognition of national health insurance coverage was 2.52 times higher in high school and 4.97 times higher in recognition toward purpose of sealant. Factor affecting recognition of national health insurance was subscription of private health insurance, recognition of sealant treatment by dental hygienist (DH) and recognition of national health insurance coverage of sealant. Attitude toward sealant treatment by DH was positive in experience of sealant, recognition of sealant treatment by DH and experience of sealant treatment by DH. Factor affecting satisfaction on the sealant by DH was recognition of sealant treatment by DH and recognition of purpose of sealant. Conclusions: To increase national health insurance coverage of sealant, it is necessary to expand positive public relations of sealant by the dental hygienist.

Comparison of Computer and Human Face Recognition According to Facial Components

  • Nam, Hyun-Ha;Kang, Byung-Jun;Park, Kang-Ryoung
    • Journal of Korea Multimedia Society
    • /
    • v.15 no.1
    • /
    • pp.40-50
    • /
    • 2012
  • Face recognition is a biometric technology used to identify individuals based on facial feature information. Previous studies of face recognition used features including the eye, mouth and nose; however, there have been few studies on the effects of using other facial components, such as the eyebrows and chin, on recognition performance. We measured the recognition accuracy affected by these facial components, and compared the differences between computer-based and human-based facial recognition methods. This research is novel in the following four ways compared to previous works. First, we measured the effect of components such as the eyebrows and chin. And the accuracy of computer-based face recognition was compared to human-based face recognition according to facial components. Second, for computer-based recognition, facial components were automatically detected using the Adaboost algorithm and active appearance model (AAM), and user authentication was achieved with the face recognition algorithm based on principal component analysis (PCA). Third, we experimentally proved that the number of facial features (when including eyebrows, eye, nose, mouth, and chin) had a greater impact on the accuracy of human-based face recognition, but consistent inclusion of some feature such as chin area had more influence on the accuracy of computer-based face recognition because a computer uses the pixel values of facial images in classifying faces. Fourth, we experimentally proved that the eyebrow feature enhanced the accuracy of computer-based face recognition. However, the problem of occlusion by hair should be solved in order to use the eyebrow feature for face recognition.

Research on Korea Text Recognition in Images Using Deep Learning (딥 러닝 기법을 활용한 이미지 내 한글 텍스트 인식에 관한 연구)

  • Sung, Sang-Ha;Lee, Kang-Bae;Park, Sung-Ho
    • Journal of the Korea Convergence Society
    • /
    • v.11 no.6
    • /
    • pp.1-6
    • /
    • 2020
  • In this study, research on character recognition, which is one of the fields of computer vision, was conducted. Optical character recognition, which is one of the most widely used character recognition techniques, suffers from decreasing recognition rate if the recognition target deviates from a certain standard and format. Hence, this study aimed to address this limitation by applying deep learning techniques to character recognition. In addition, as most character recognition studies have been limited to English or number recognition, the recognition range has been expanded through additional data training on Korean text. As a result, this study derived a deep learning-based character recognition algorithm for Korean text recognition. The algorithm obtained a score of 0.841 on the 1-NED evaluation method, which is a similar result to that of English recognition. Further, based on the analysis of the results, major issues with Korean text recognition and possible future study tasks are introduced.