• Title/Summary/Keyword: Image Discrimination

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ART2 Based Fuzzy Binarization Method with Low Information Loss (정보손실이 적은 ART2 기반 퍼지 이진화 방법)

  • Kim, Kwang-Baek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.6
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    • pp.1269-1274
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    • 2014
  • In computer vision research, binarization procedure is one of the most frequently used tools to discriminate target objects from background in grey level binary image. Fuzzy binarization is a reliable technique in environment with high uncertainty such as medical image analysis by setting the threshold as the average of minimum and maximum brightness with triangle type fuzzy membership function. However, this technique is also known as contrast sensitive method thus its discrimination power is not so great when the image has low contrast difference between objects and backgrounds and suffer from information loss as a result. Thus, in this paper, we propose a fuzzy binarization using ART2 algorithm to handle such low contrast image analysis. Proposed ART2 algorithm is applied to determine the medium point of membership function in the fuzzy binarization paradigm. The proposed methods shows low information loss rate in our experiment.

The effect on purchasing intention of Hotel Brand-image and Choice-attribution (호텔 브랜드이미지와 선택속성이 구매의도에 미치는 영향에 관한 연구)

  • Lee, Ji-Yeong;Kim, Tae-Jin
    • Journal of Applied Tourism Food and Beverage Management and Research
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    • v.16 no.1
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    • pp.43-69
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    • 2005
  • Generally, brand is the title for discriminating their own goods and service from other competitive company, brand-image means customer's good and bad affection or loyalty the brand of specific company. Customers often choose the goods according to the value of goods brand. In terms of this viewpoint, the value of company's brand is very important factor to the company's success. Brand-image also effects customers on selling company's goods. Specially, to the hotel business that should ensure lots of customer for a long period with the interest and credit of customers, its brand-image is more significant. What the image is looked upon as a important factor in marketing is due to the difficulty of discrimination against goods standardized in price and quality. Therefore, the company's image acts as a more important marketing factor in the high industrial society. Also it means a lot to the customer's purchasing behavior. When the company's brand-image is recognized or discriminated, customer's memory is longer and customer's reliability is raised than other company's advertisement and public information. Nowadays, most of hotels are perceiving the importance on their own brand-image but in the lack of deep study and systematic strategy in reality. The purpose of this study is to research the effect on customer's purchasing intention of hotel brand-image and choice-attribution. The empirical research has been done from 23April, 2004 to 20May, 2004. Data were collected from general customers who are using hotel located in Taegu. In conclusion, hotel brand-image depends highly on, the service quality of hotel staff and reputation of hotel. Besides, this acts on customer's hotel choice decisively.

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Recognition of Thyroid Gland Cancer Cells using Fuzzy Logic and Genetic Algorithms (퍼지 논리와 유전 알고리듬을 이용한 갑상선 암세포의 인식)

  • 나철훈
    • Journal of Biomedical Engineering Research
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    • v.22 no.3
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    • pp.217-222
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    • 2001
  • This paper proposes the new method based on fuzzy logic which recognizes between normal, and abnormal(two types of abnormal : follicular neoplastic, and papillary neoplastic) of thyroid gland cells from pre-obtained 16 feature parameters of image data. This paper applies the genetic algorithms to obtain the dominant feature parameters which have a great influence on discrimination between normal and abnormal cells. This paper shows the effectiveness of proposed method to 240 thyroid gland cells(60 normal cells, 120 follicular neoplastic cells and 60 papillary neoplastic cells) and new dominant feature parameters obtained by genetic algorithms. As a consequence of using the proposed method, average recognition rate of 88.75 % was obtained.

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A Vowel Discrimination of Korean Monophthongs [i, e, a, o, u, ${\omega}$] Using Vocal Tract Magnetic Resonance Image and F1/F2 (성도 자기공명 영상과 음향정보(F1/F2)를 이용한 한국어 단모음 [이, 에, 아, 오, 우, 으] 판별)

  • Seong, Cheol-Jae;Park, Jong-Won;Kim, Gui-Ryong
    • MALSORI
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    • no.56
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    • pp.103-125
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    • 2005
  • We present a new method of measuring the volume and cross-sectional area of the vocal tract from magnetic resonance images. The vocal tract was divided by the 2 constriction points on the horizontal and vertical planes. The ratios of the volumes of the segment vocal tracts to that of the entire vocal tract play a crucial role in discriminating Korean monophthongs in that vowels were successfully discriminated by the ratios. The discriminant analysis also demonstrated that the acoustic parameters F1 and F2, in addition to the segment volumes, serve as significant parameters in discriminating Korean monophthongs.

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Fuzzy Neural Network-Based Noisiness Decision of Road Scene for Lane Detection (퍼지신경망을 이용한 도로 씬의 차선정보의 잡음도 판별)

  • Yi, Un-Kun;Baek, Kwang-Ryul;Kwon, Seok-Geon;Lee, Joon-Woong
    • Proceedings of the KIEE Conference
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    • 2000.11d
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    • pp.761-764
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    • 2000
  • This paper presents a Fuzzy Neural Network (FNN) system to decide whether or not the right information of lanes can be extracted from gray-level images of road scene. The decision of noisy level of input images has been required because much noises usually deteriorates the performance of feature detection based on image processing and lead to erroneous results. As input parameters to FNN, eight noisiness indexes are constructed from a cumulative distribution function (CDF) and proved the indexes being classifiers of images as the good and the bad corrupted by sources of noise by correlation analysis between input images and the indexes. Considering real-time processing and discrimination efficiency, the proposed FNN is structured by eight input parameters, three fuzzy variables and single output. We conduct much experiments and show that our system has comparable performance in terms of false-positive rates.

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Similar and rotation invariant optical pattern recognition characteristics of SA-MPOF (SA-MPOF의 유사 및 회전불변 광패턴인식 특성)

  • Yeun, Jin-Seon;Lee, Yeon-Seon;Kim, Nam;Um, Joo-Uk;Park, Han-Kyu
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.4
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    • pp.855-868
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    • 1996
  • In this paper, multiplhase only filter(MPOFs) are designed using simulated annealing algorithm. These filters have excellent recognition characteristics for similar patterns or rotated patterns and enhance optical efficiency as well as spatial-bandwidth product by deleting mirror image. As the result of computer simulation to certify recogntion characteristics of similar patterns, simulated annealing-MPOF(SA-MPOF) has superior discrimination and higher correlation peak values than cosine binary phase only filters(CBPOF) and simpulated annealing-BPOF (SA-BPOF). THe filter having training process for rotated patterns of arbitraty possible angle can overcome that phase only filter(POF) and CBPOF can't recognize rotated input patterns.

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Extraordinary State Discrimination of Grinding Wheel Surface Using Pattern Classification (패턴 분류법을 이용한 연삭 숫돌면의 이상상태 판별)

  • 유은이
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2000.04a
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    • pp.447-452
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    • 2000
  • The grinding plays a key role which decide the quality of a product finally. But the grinding process is very irregular, so it is very difficult to analyse the process accurately. Therefore it is very important in the aspect of precision and automation to reduce the idle time and to decide the proper dressing time by visualizing. In this study, we choose the direct method of observation by making use of computer vision, and apply pattern classification technique to the method of measuring the wheel surface. Pattern classification technique is proper to analyse complex surface image. We observe the change of the wheel surface by making use of the gray level run lengths which are representative prince in this technique.

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A study of Leather Quality Discrimination Algorithm Using a Surface Curvature Image(I) (표면의 굴곡 특징을 이용한 피혁 자동 등급 선별 알고리즘에 관한 연구( I ))

  • 이명수;이규동;김광섭;이진록;권장우
    • Proceedings of the Korea Multimedia Society Conference
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    • 2000.11a
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    • pp.209-213
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    • 2000
  • 피혁 제품의 품질을 결정함에 있어 제일 중요한 요인은 눈에 보이는 표면상태이다. 지금까지는 피혁공장에서 대부분의 피혁을 육안으로 선별하여 오고 있는데 이러한 방법은 등급을 구분하는데 많은 노동력과 시간이 소모되고, 일관성이 부족할 뿐만 아니라 미세한 결함이나 정밀한 치수를 감지할 수가 없어 그 등급의 품질에 문제가 발생한다. 이런 문제를 해결하기 위해 본 논문에서는 실시간 영상처리와 AI를 이용하여 피혁 자동 등급 선별 시스템을 설계하고자 한다. 제안한 선별 시스템의 설계는 세계 피혁업계와 차별을 기하고 검사시간을 단축하여 생산 효율성을 증대하면, 등급의 표준화 및 품질의 고급화를 도모할 수 있다.

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Seafloor Classification Based on the Texture Analysis of Sonar Images Using the Gabor Wavelet

  • Sun, Ning;Shim, Tae-Bo
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.3E
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    • pp.77-83
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    • 2008
  • In the process of the sonar image textures produced, the orientation and scale factors are very significant. However, most of the related methods ignore the directional information and scale invariance or just pay attention to one of them. To overcome this problem, we apply Gabor wavelet to extract the features of sonar images, which combine the advantages of both the Gabor filter and traditional wavelet function. The mother wavelet is designed with constrained parameters and the optimal parameters will be selected at each orientation, with the help of bandwidth parameters based on the Fisher criterion. The Gabor wavelet can have the properties of both multi-scale and multi-orientation. Based on our experiment, this method is more appropriate than traditional wavelet or single Gabor filter as it provides the better discrimination of the textures and improves the recognition rate effectively. Meanwhile, comparing with other fusion methods, it can reduce the complexity and improve the calculation efficiency.

Efficient Korean Character Recognition using Partial Distortion Invariant MACE Composite Filter (제한된 왜곡불변 MACE 합성필터를 이용한 효율적인 한글 문자 인식)

  • 김성용;이승희;김철수;김정우;배장근;김수중
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.4
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    • pp.44-55
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    • 1993
  • In this paper, we proposed a new optical method for the efficient recognition of Korean characters. There are six filters in the proposed method which employed the concepts of amplitude-modulated phase-only filter(AMPOF) and spatial frequency modulation(SFM). Here, amplitude modulation is used to achieve improved correlation discrimination and SFM is to reduce the number of filters. We also used a simplified synthetic discriminant function(SDF) for distortion invariance of input image. In order to recognize the partial rotation invariant Korean characters, the proposed distortion invariant minimum average correlation energy (MACE) filter is synthesized SFM, partial rotation invariant filter (PRIF), AMPOF and MACE for partial rotation invariance in the frequency domain. The advantage of the proposed filters is to supress the sidelobes of cross correlation peak away from the autocorrelation peak and to produce sharp correlation peaks. We performed simulation and optical experiment for some of Korea characters using the proposed method. The results show that the proposed method has more improved discriminant ability and reduced processing time than the conventional methods.

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