• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.556-559
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• 1999

This paper proposes an hybrid person identification algorithm utilizing finger crease pattern and finger thickness profiles. We have observed that by adding finger thickness profiles as a feature vector, we could improve the performance of the person identification system utilizing only finger crease pattern. We presented the comparative evaluation of the proposed algorithm in detail.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.187-192
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• 2023

With development of information technology and necessity for high security, using different identification methods has become very important. Each biometric feature has its own advantages and disadvantages and choosing each of them depends on our usage. Retinal scanning is a bio scale method for identification. The retina is composed of vessels and optical disk. The vessels distribution pattern is one the remarkable retinal identification methods. In this paper, a new approach is presented for identification via retinal images using LBP and hog methods. In the proposed method, it will be tried to separate the retinal vessels accurately via machine vision techniques which will have good sustainability in rotation and size change. HOG-based or LBP-based methods or their combination can be used for separation and also HSV color space can be used too. Having extracted the features, the similarity criteria can be used for identification. The implementation of proposed method and its comparison with one of the newly-presented methods in this area shows better performance of the proposed method.

• 대한임베디드공학회논문지
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• 제12권6호
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• pp.395-403
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• 2017

Image processing for object detection and identification has been studied for supply chain management application with various approaches. Among them, feature pointed detection algorithm is used to track an object or to recognize a position in automated supply chain systems and a depth image based feature point detection is recently highlighted in the application. The result of feature point detection is easily influenced by image noise. Also, the depth image has noise itself and it also affects to the accuracy of the detection results. In order to solve these problems, we propose a novel hybrid filtering mechanism for depth image based feature point detection, it shows better performance compared with conventional hybrid filtering mechanism.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2002년도 춘계종합학술대회
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• pp.448-451
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• 2002

본 연구는 인식의 정확성을 향상시키기 위하여 단일 특징을 이용한 인식 대신에 다중 특징을 이용하는 인식방법을 제안한다. 각각의 특징은 다음과 같은 방법으로 구하여진다. 얼굴 전체의 특징은 웨이블렛 다해상도 분해와 주성분 분석방법으로 계산하였고, 입술의 경우는 입술의 경계를 구한 후 최소 자승법을 이용한 방정식의 계수를 구하였으며, 또 하나의 특징은 얼굴요소의 거리 비율에 의해 구하였다. 위 값들을 입력으로 한 역전파 학습 알고리즘으로 분류하여 실험하여 제안된 방범의 유효성을 확인하였다.

• Journal of information and communication convergence engineering
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• 제5권3호
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• pp.233-238
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• 2007

An approach to identify Chinese event types is proposed in this paper which combines a good feature selection policy and a Maximum Entropy (ME) model. The approach not only effectively alleviates the problem that classifier performs poorly on the small and difficult types, but improve overall performance. Experiments on the ACE2005 corpus show that performance is satisfying with the 83.5% macro - average F measure. The main characters and ideas of the approach are: (1) Optimal feature set is built for each type according to local feature selection, which fully ensures the performance of each type. (2) Positive and negative features are explicitly discriminated and combined by using one - sided metrics, which makes use of both features' advantages. (3) Wrapper methods are used to search new features and evaluate the various feature subsets to obtain the optimal feature subset.

• 한국정보통신학회논문지
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• 제7권4호
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• pp.705-711
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• 2003

본 논문에서는 자동적으로 얼굴과 얼굴 특징점(FFPs:Facial Feature Points)을 검출하는 시스템을 제안하였다. 얼굴은 Gabor 특징에 의하여 지정된 특징점의 교점 그래프와 공간적 연결을 나타내는 에지 그래프로 표현하였으며 제안된 탄력적 특징 정합은 모델과 입력 영상에 상응하는 특징을 취하였다. 또한, 정합 모델은 국부적으로 경쟁적이고 전체적으로 협력적인 구조를 이룸으로서 영상공간에서 불규칙 확산 처리와 같은 역할을 하도록 하였으며, 복잡한 배경이나 자세의 변화, 그리고 왜곡된 얼굴 영상에서도 원활하게 동작하는 얼굴 식별 시스템을 구성함으로서 제안된 방법의 효율성을 증명하였다.

• Journal of Multimedia Information System
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• 제9권1호
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• pp.1-10
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• 2022

China is a big country in animal fur industry. The total production and consumption of fur are increasing year by year. However, the recognition of fur in the fur production process still mainly relies on the visual identification of skilled workers, and the stability and consistency of products cannot be guaranteed. In response to this problem, this paper proposes a feature fusion-based animal fur recognition network on the basis of typical convolutional neural network structure, relying on rapidly developing deep learning techniques. This network superimposes texture feature - the most prominent feature of fur image - into the channel dimension of input image. The output feature map of the first layer convolution is inverted to obtain the inverted feature map and concat it into the original output feature map, then Leaky ReLU is used for activation, which makes full use of the texture information of fur image and the inverted feature information. Experimental results show that the algorithm improves the recognition accuracy by 9.08% on Fur_Recognition dataset and 6.41% on CIFAR-10 dataset. The algorithm in this paper can change the current situation that fur recognition relies on manual visual method to classify, and can lay foundation for improving the efficiency of fur production technology.

• 음성과학
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• 제15권1호
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• pp.37-51
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• 2008

The main goal of this study is to examine if there is a difference in the utilization of a vowel length cue between Korean and Japanese L2 learners of English in their perception and production of postvocalic coda contrast in English. Given that Japanese subjects' performances on the identification and production tasks were much better than Korean subjects' performance, we may support the prediction based on the Feature Hypothesis which maintains that L1 phonological features can facilitate the perception of L2 acoustic cue. Since vowel length contrast is a phonological feature in Japanese but not in Korean, the tasks, which assess L2 leaners' ability to discriminate vowel length contrast in English, are much easier for the Japanese group than for the Korean group. Although the Japanese subjects demonstrated a better performance than the Korean subjects, the performance of the Japanese group was worse than that of the English control group. This finding implies that L2 learners, even Japanese learners, should be taught that the durational difference of the preceding vowels is the most important cue to differentiate postvocalic contrastive codas in English.

• 한국해양공학회지
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• 제22권1호
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• pp.30-36
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• 2008

Underwater ambient noise originating from geophysical, biological, and man-made acoustic sources contains information on the source and the ocean environment. Such noise affectsthe performance of sonar equipment. In this paper, three steps are used to identify the ambient noise source, detection, feature extraction, and similarity measurement. First, we use the zero-crossing rate to detect the ambient noisesource from background noise. Then, a set of feature vectors is proposed forthe ambient noise source using the Hilbert-Huang transform and the Karhunen-Loeve transform. Finally, the Euclidean distance is used to measure the similarity between the standard feature vector and the feature vector of the unknown ambient noise source. The developed algorithm is applied to the observed ocean data, and the results are presented and discussed.

• 한국정보전자통신기술학회논문지
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• 제3권2호
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• pp.12-17
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• 2010

본 논문에서는 자동적으로 얼굴 특징점을 검출하는 시스템을 제안하였다. 얼굴은 Gabor 특징에 의하여 지정된 특징점의 교점 그래프와 공간적 연결을 나타내는 에지 그래프로 표현하였으며, 제안된 탄력적 특징 정합은 모델과 입력 영상에 상응하는 특징을 취하였다. 정합 모델은 국부적으로 경쟁적이고 전체적으로 협력적인 구조를 이룸으로서 영상공간에서 불규칙 확산 처리와 같은 역할을 하도록 하였다. 복잡한 배경이나 자세의 변화, 그리고 왜곡된 얼굴 영상에서도 원활하게 동작하는 얼굴 식별 시스템을 구성함으로서 제안된 방법의 효율성을 증명하였다.