• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.509-515
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• 2004

In this paper we present the linear combination of a fuzzy opening and closing filter with locally adaptive structuring elements that can preserve the geometrical features of an image. Based on the adaptation algorithm of linear combination of the fuzzy opening and closing filter, the optimal structuring element for image representation is obtained. The optimal structuring element is an indicator of the shape and direction of an object's image, which is useful in filtering, multi resolution, segmentation, and recognition of an image.

• 한국멀티미디어학회논문지
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• 제23권4호
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• pp.581-587
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• 2020

In this study, we investigated the correlation between logotype elements and brand recognition among corporate logos using quantification methodology 2. In addition, this study wanted to find out if consumers could easily recognize the product according to the design elements of the logotype. Our study showed that feminine tendency in logotype design was associated with clothes and cosmetics and masculine design element that will make people recall the game and health products. There were clothes and cosmetics for men but feminine design factor was strongly associated with clothes and cosmetics. In other words, logotype for cosmetic and clothing needed to be feminine by using neutral and cold colors. The relationship between the logotype and related products affected the brand recognition and this result can be used as a key element of corporate marketing.

• 한국정보처리학회논문지
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• 제5권1호
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• pp.119-127
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• 1998

본 논문에서는 한글 인쇄체 인식 시스템의 실시간 처리를 위하여 인식 프로세스중 시간이 많이 걸리는 한글 문자 유형 분류 및 자소 인식 단계를 고속 처리할 수 있는 다층구조 신경망을 VLSI 설계 하였으며, 신경망과 호스트 컴퓨터간의 인터페이스와 신경망 제어를 담당하는 코프로세서 구조를 제안하였다. 이를 VHDL 모델링 및 논리합성을 통하여 설계하여 시뮬레이션을 통하여 구조와 동작 및 성능을 검증하였다. 실험결과 제안한 신경망 coprocessor는 기존의 소프트웨어 구현 인식 시스템의 유형 분류 및 자소 인식률과 대등한 성능을 보인 반면 고속의 인식속도를 보였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권3호
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• pp.322-326
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• 2004

This paper describes a new iris recognition method based on a shift-invariant wavelet sub-images. For the feature representation, we first preprocess an iris image for the compensation of the variation of the iris and for the easy implementation of the wavelet transform. Then, we decompose the preprocessed iris image into multiple subband images using a shift-invariant wavelet transform. For feature representation, we select a set of subband images, which have rich information for the classification of various iris patterns and robust to noises. In order to reduce the size of the feature vector, we quantize. each pixel of subband images using the Lloyd-Max quantization method Each feature element is represented by one of quantization levels, and a set of these feature element is the feature vector. When the quantization is very coarse, the quantized level does not have much information about the image pixel value. Therefore, we define a new similarity measure based on mutual information between two features. With this similarity measure, the size of the feature vector can be reduced without much degradation of performance. Experimentally, we show that the proposed method produced superb performance in iris recognition.

• 한국멀티미디어학회논문지
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• 제23권12호
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• pp.1552-1564
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• 2020

As various styles of fonts were used, there were problems such as output errors due to uninstalled fonts and difficulty in font recognition. To solve these problems, research on font recognition and recommendation were actively conducted. However, Hangul font research remains at the basic level. Therefore, in order to automate the comparison on Hangul font similarity in the future, we analyze the influence of each stroke element property. First, we select seven representative properties based on Hangul stroke shape elements. Second, we design a calculation model to compare similarity between fonts. Third, we analyze the effect of each stroke element through the cosine similarity between the user's evaluation and the results of the model. As a result, there was no significant difference in the individual effect of each representative property. Also, the more accurate similarity comparison was possible when many representative properties were used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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• pp.1076-1094
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• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.

• 대한전자공학회논문지
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• 제12권2호
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• pp.11-17
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• 1975

이 논문은 한글문자의 자동인식을 위한 기초적인 연구로서 기본문자의 구조에 대해서 검토하였다. 기본문자를 구조, 선분구조 및 물자 graph의 node와의 연결곤계 들 구조를 세가지 측면에서 집합 및 군론에 의한 대수적인 분석을 하고 또 그들의 각 구조의 복잡성에 대한 계릉을 고찰하였다. 나아가서 10개의 모음은 한 요소의 Affine 변환에 의한 연속회전으로 이루어지는 회전변환군 속에서 다수의 동치관계가 존재한다는 것을 기술하므로써, 한글문자의 인식에 있어서는 topological 골격외에 기하적 성질이 특히 중요하다는 것을 아울러 지적 하였다. The paper examined the character structure as a basic study for the recognition of Korean characters. In view of concave structure, line structure and node relationship of character graph, the algebraic structure of the basic Korean characters is are analized. Also, the degree of complexities in their character structure is discussed and classififed. Futhermore, by describing the fact that some equivalence relations are existed between the 10 vowels of rotational transformation group by Affine transformation of one element into another, it could be pointed out that the geometrical properting in addition to the topological properties are very important for the recognition of Korean characters.

• 한국지능시스템학회논문지
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• 제11권6호
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• pp.510-515
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• 2001

일반적으로 음성신호로부터 사람의 감정을 인식할 수 있는 요소는(1)대화의 내용에 사용한 단어, (2)톤 (tore), (3)음성신호의 피치(Pitch), (4)포만트 주파수(Formant Frequencey)그리고 (5)말의 빠르기(Speech Speed)(6)음질(Voice Quality)등이다. 사람의 경우는주파수 같은 분석요소 보다 톤과 단어 빠르기, 음질로 감정을 받아들이게 되는것이 자연스러운 방법이므로 당연히 후자의 요소들이 감정을 분류하는데 중요한 인자로쓰일 수있다. 그리고, 종래는 주로 후자의 효소들을 이용하였는데, 기계로써 구현하기 위해서는 포만트 주파수를 사용할 수있게 되는것이 도움이 된다. 그러므로, 본 연구는 음성 신호로부터 피치와 포만트, 그리고 말의 빠르기 등을 이용하여 감성인식시스템을 구현하는것을 목표로 연구를 진행하고 있으며, 그 1단계 연구로서 본 논문에서는 화가 나서 내뱉는 말을 기반으로 하여 화난 감정의 독특한 특성을 찾아내었다.

• 전자공학회논문지B
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• 제32B권8호
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• pp.1127-1136
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• 1995

In this paper, a morphological shape decomposition method is proposed for the purpose of pattern recognition and image compression. In the method, a structuring element that geometrical characteristics is more similar to the shape function is preselected. The shape is decomposed into the primitive elements corresponding to the structuring element. A gray scale image also is transformed into 8 bit plane images for the hierarchical reconstruction required in image communication systems. The shape in each bitplane is decomposed to the proposed method. Through the experiment. it is proved that the description error is reduced and the coding efficiency is improved.

• 전자공학회논문지B
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• 제33B권10호
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• pp.63-71
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• 1996

This paper proposes a method which analyzes facial shape and extracts positions of eyes regardless of the tilt and the size of input iamge. With the extracted feature parameters of facial element by the method, full human faces are recognized by a neural network which BP algorithm is applied on. Input image is changed into binary codes, and then labelled. Area, circumference, and circular degree of the labelled binary image are obtained by using chain code and defined as feature parameters of face image. We first extract two eyes from the similarity and distance of feature parameter of each facial element, and then input face image is corrected by standardizing on two extracted eyes. After a mask is genrated line historgram is applied to finding the feature points of facial elements. Distances and angles between the feature points are used as parameters to recognize full face. To show the validity learning algorithm. We confirmed that the proposed algorithm shows 100% recognition rate on both learned and non-learned data for 20 persons.