• Title/Summary/Keyword: Picture Recognition

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Image Recognition Using Colored-hear Transformation Based On Human Synesthesia (인간의 공감각에 기반을 둔 색청변환을 이용한 영상 인식)

  • Shin, Seong-Yoon;Moon, Hyung-Yoon;Pyo, Seong-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.2
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    • pp.135-141
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    • 2008
  • In this paper, we propose colored-hear recognition that distinguishing feature of synesthesia for human sensing by shared vision and specific sense of hearing. We perceived what potential influence of human's structured object recognition by visual analysis through the camera, So we've studied how to make blind persons can feel similar vision of real object. First of all, object boundaries are detected in the image data representing a specific scene. Then, four specific features such as object location in the image focus, feeling of average color, distance information of each object, and object area are extracted from picture. Finally, mapping these features to the audition factors. The audition factors are used to recognize vision for blind persons. Proposed colored-hear transformation for recognition can get fast and detail perception, and can be transmit information for sense at the same time. Thus, we were get a food result when applied this concepts to blind person's case of image recognition.

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An Analysis of Recognition and Preference for the View in an Apartment Unit (아파트 단위세대에서 보이는 경관에 대한 인지 및 선호 특성)

  • Moon, Ji-Won;Ha, Jae-Myung
    • Journal of the Korean housing association
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    • v.18 no.1
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    • pp.83-93
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    • 2007
  • Following the previous ones, this study is intended to explore methods of qualitative assessment on the view from apartment units. It first complemented and analyzed the attributes of landscape elements and then set up questionnaire items based on these attributes to identify the tendencies in apartment inhabitants' recognition of landscape elements, and then conducted a preference assessment on the test cases sampled on the basis of picture and other data collected in the previous studies to identify the characteristics of the preference for the view from apartment units according to landscape elements. Consequently, the following results have been derived. First, the landscape elements seen from apartment units may be classified into a total of sixteen categories, and the overall ratio of natural elements to artificial ones is shown to be approximately one to three. Second, it is also shown that apartment dwellers tend to prefer natural landscape elements over artificial ones, and the preferences for the distance to and location of landscape elements exhibit certain variance depending on the type of the elements. Third, the analysis of the preference for landscape elements has revealed that the types of landscape elements, the make-up and diversity of landscape elements, and the perceived distance to landscape elements as well as the resultant feeling of openness all affect the preference tendencies.

A Study on Face Recognition using a Hybrid GA-BP Algorithm (혼합된 GA-BP 알고리즘을 이용한 얼굴 인식 연구)

  • Jeon, Ho-Sang;Namgung, Jae-Chan
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.2
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    • pp.552-557
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    • 2000
  • In the paper, we proposed a face recognition method that uses GA-BP(Genetic Algorithm-Back propagation Network) that optimizes initial parameters such as bias values or weights. Each pixel in the picture is used for input of the neuralnetwork. The initial weights of neural network is consist of fixed-point real values and converted to bit string on purpose of using the individuals that arte expressed in the Genetic Algorithm. For the fitness value, we defined the value that shows the lowest error of neural network, which is evaluated using newly defined adaptive re-learning operator and built the optimized and most advanced neural network. Then we made experiments on the face recognition. In comparison with learning convergence speed, the proposed algorithm shows faster convergence speed than solo executed back propagation algorithm and provides better performance, about 2.9% in proposed method than solo executed back propagation algorithm.

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An Implementation of Device Connection and Layout Recognition Techniques for the Multi-Display Contents Delivery System (멀티 디스플레이 콘텐츠 전송 시스템을 위한 디바이스 연결 및 배치 인식 기법의 구현)

  • Jeon, So-yeon;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.19 no.8
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    • pp.1479-1486
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    • 2016
  • According to the advancement of display devices, the multi-screen contents display environment is growing to be accepted for the display exhibition area. The objectives of this research are to find communications technology and to design an editor interface of contents delivery system for the larger and adaptive multi-display workspaces. The proposed system can find existence of display devices and get information without any additional tools like marker, and can recognize device layout with only web-cam and image processing technology. The multi-display contents delivery system is composed of devices with three roles; display device, editor device, and fixed server. The editor device which has the role of main control uses UPnP technology to find existence and receive information of display devices. extract appointed color in captured picture using a tracking library to recognize the physical layout of display devices. After the device information and physical layout of display devices are connected, the content delivery system allows the display contents to be sent to the corresponding display devices through WebSocket technology. Also the experimental results show the possibility of our device connection and layout recognition techniques can be utilized for the large spaced and adaptive multi-display applications.

Distance measurement technique using a mobile camera for object recognition (객체 인식을 위한 이동형 카메라를 이용한 거리 측정 기법)

  • Hwang, Chi-gon;Lee, Hae-Jun;Yoon, Chang-Pyo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.352-354
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    • 2022
  • Position measurement using a camera has been studied for a long time. This is being studied for distance recognition or object recognition in autonomous vehicles, and it is being studied in the field of indoor navigation, which is a limited space where GPS is difficult to apply. In general, in a method of measuring the distance using a camera, the distance is measured using a distance between the cameras using two stereo cameras and a value measured through a captured image or photo. In this paper, we propose a method of measuring the distance of an object using a single camera. The proposed method measures the distance by using the distance between cameras, such as a stereo camera, and the value measured by the photographed picture through the gap of the photographing time and the distance between photographing.

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Recognition of Resident Registration Card using ART2-based RBF Network and face Verification (ART2 기반 RBF 네트워크와 얼굴 인증을 이용한 주민등록증 인식)

  • Kim Kwang-Baek;Kim Young-Ju
    • Journal of Intelligence and Information Systems
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    • v.12 no.1
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    • pp.1-15
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    • 2006
  • In Korea, a resident registration card has various personal information such as a present address, a resident registration number, a face picture and a fingerprint. A plastic-type resident card currently used is easy to forge or alter and tricks of forgery grow to be high-degree as time goes on. So, whether a resident card is forged or not is difficult to judge by only an examination with the naked eye. This paper proposed an automatic recognition method of a resident card which recognizes a resident registration number by using a refined ART2-based RBF network newly proposed and authenticates a face picture by a template image matching method. The proposed method, first, extracts areas including a resident registration number and the date of issue from a resident card image by applying Sobel masking, median filtering and horizontal smearing operations to the image in turn. To improve the extraction of individual codes from extracted areas, the original image is binarized by using a high-frequency passing filter and CDM masking is applied to the binaried image fur making image information of individual codes better. Lastly, individual codes, which are targets of recognition, are extracted by applying 4-directional contour tracking algorithm to extracted areas in the binarized image. And this paper proposed a refined ART2-based RBF network to recognize individual codes, which applies ART2 as the loaming structure of the middle layer and dynamicaly adjusts a teaming rate in the teaming of the middle and the output layers by using a fuzzy control method to improve the performance of teaming. Also, for the precise judgement of forgey of a resident card, the proposed method supports a face authentication by using a face template database and a template image matching method. For performance evaluation of the proposed method, this paper maked metamorphoses of an original image of resident card such as a forgey of face picture, an addition of noise, variations of contrast variations of intensity and image blurring, and applied these images with original images to experiments. The results of experiment showed that the proposed method is excellent in the recognition of individual codes and the face authentication fur the automatic recognition of a resident card.

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FACE DETECTION USING SKIN-COLOR MODEL AND SUPPORT VECTOR MACHINE

  • Seld, Yoko;Yuyama, Ichiro;Hasegawa, Hiroshi;Watanabe, Yu
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.592-595
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    • 2009
  • In this paper, we propose a face detection technique for still pictures which sequentially uses a skin-color model and a support vector machine (SVM). SVM is a learning algorithm for solving the classification problem. Some studies on face detection have reported superior results of SVM over neural networks. The SVM method searches for a face in a picture while changing the size of the window. The detection accuracy and the processing time of SVM vary largely depending on the complexity of the background of the picture or the size of the face. Therefore, we apply a face candidate area detection method using a skin-color model as a preprocessing technique. We compared the method using SVM alone with that of the proposed method in respect to face detection accuracy and processing time. As a result, the proposed method showed improved processing time while maintaining a high recognition rate.

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A Propensity of Formative Presentation by Line Drawing (라인드로잉에 의한 디자인 조형의 표현성향)

  • 우흥룡
    • Archives of design research
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    • v.11 no.2
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    • pp.95-103
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    • 1998
  • During design thinking and developing, its idea into the real world, and we are under pattern recognition and gestalt principles of perceptual organization. Generally originality is a part of creativity which consists an integral factor of the designing. This is a study on the measure system for an ability of originality in design. It is reorganized that the OTLD(Originality Test of Line Drawing) is a measuring system for personal originality. In order to catch the development the thoughts, we presented 10 picture planes as stimuli (each picture plane contained 3-18 dots), recorded the tape displaying eye-mark trajectories and outputting the trajectories with EMR(Eye Mark Recorder), then found the process of visual sensation and perception. From the results of this study, we examined the relationships between connections and complexity of the objects on the picture plane, which could be transformed into some objective measuring parameters. We would suggest this OLTD as a measurement system for an ability of originality in design fields, but we couldn't find any reliability and validity for fine art fields.

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Phonological awareness skills in terms of visual and auditory stimulus and syllable position in typically developing children (청각적, 시각적 자극제시 방법과 음절위치에 따른 일반아동의 음운인식 능력)

  • Choi, Yu Mi;Ha, Seunghee
    • Phonetics and Speech Sciences
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    • v.9 no.4
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    • pp.123-128
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    • 2017
  • This study aims to compare the performance of syllable identification task according to auditory and visual stimuli presentation methods and syllable position. Twenty-two typically developing children (age 4-6) participated in the study. Three-syllable words were used to identify the first syllable and the final syllable in each word with auditory and visual stimuli. For the auditory stimuli presentation, the researcher presented the test word only with oral speech. For the visual stimuli presentation, the test words were presented as a picture, and asked each child to choose appropriate pictures for the task. The results showed that when tasks were presented visually, the performances of phonological awareness were significantly higher than in presenting with auditory stimuli. Also, the performances of the first syllable identification were significantly higher than those of the last syllable identification. When phonological awareness task are presented by auditory stimuli, it is necessary to go through all the steps of the speech production process. Therefore, the phonological awareness performance by auditory stimuli may be low due to the weakness of the other stages in the speech production process. When phonological awareness tasks are presented using visual picture stimuli, it can be performed directly at the phonological representation stage without going through the peripheral auditory processing, phonological recognition, and motor programming. This study suggests that phonological awareness skills can be different depending on the methods of stimulus presentation and syllable position of the tasks. The comparison of performances between visual and auditory stimulus tasks will help identify where children may show weakness and vulnerability in speech production process.

Study on Weight Summation Storage Algorithm of Facial Recognition Landmark (가중치 합산 기반 안면인식 특징점 저장 알고리즘 연구)

  • Jo, Seonguk;You, Youngkyon;Kwak, Kwangjin;Park, Jeong-Min
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.1
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    • pp.163-170
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    • 2022
  • This paper introduces a method of extracting facial features due to unrefined inputs in real life and improving the problem of not guaranteeing the ideal performance and speed of the object recognition model through a storage algorithm through weight summation. Many facial recognition processes ensure accuracy in ideal situations, but the problem of not being able to cope with numerous biases that can occur in real life is drawing attention, which may soon lead to serious problems in the face recognition process closely related to security. This paper presents a method of quickly and accurately recognizing faces in real time by comparing feature points extracted as input with a small number of feature points that are not overfit to multiple biases, using that various variables such as picture composition eventually take an average form.