• 대한전자공학회논문지SP
• /
• 제40권6호
• /
• pp.10-19
• /
• 2003

현재 상용화된 지문인식 시스템은 지문 입력기를 구동하는데 필요한 함수가 표준화 되어있지 않기 때문에 입력기 사이의 호환이 불가능하다. 본 연구의 목적은 지문인식 시스템이 대중화됨에 따라 앞으로 지문인식 시장에서 수요가 예상되는 다양한 지문 입력기 사이의 지문인식이 가능한 시스템의 개발이다. 본 논문에서는 광학식, 반도체식, 열감지 방식의 지문 입력기를 대상으로 하여 지문인식 시스템을 설계 구현하였으며, 융선 개수 정보의 추출 방법과 융선 개수 정보를 이용한 정합 방법을 제안하였다.

• 한국정보통신학회논문지
• /
• 제10권5호
• /
• pp.877-889
• /
• 2006

교통제어나 차량에 연관된 범죄 등에서 자동차의 인식에 관한 연구의 중요성 때문에 이에 관련된 연구는 오래전부터 수행되어 왔다. 본 논문에서는 차량이 주행할 때의 정보와 영상을 획득하여 제조회사별 차종을 인식하는 방법을 제안하고자 한다. 본 논문의 차종인식은 차량의 압력을 이용한 차폭 검출방법, 그리고 보다 더 정확한 인식률을 얻기 위한 레이저 거리계를 이용한 차고 검출방법, $3\sim5$종의 구별을 위 한 차량의 번호판 인식 방법을 조합함으로써 차량 인식의 오류를 줄이는 시스템을 구현하였다. 구현된 차종인식 시스템은 2차원 CCD에 의한 차량의 영상획득과 이를 통한 다양한 영상처리 알고리즘에 의해서 국내의 전 차종에 적용할 수 있으며, 실제의 실험 결과는 높은 인식률을 나타내었다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권5호
• /
• pp.1856-1869
• /
• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권7호
• /
• pp.2356-2376
• /
• 2021

In this paper, we proposed a novel modulation recognition method based on quantum elephant herding algorithm (QEHA) evolving neural network under impulse noise environment. We use the adaptive weight myriad filter to preprocess the received digital modulation signals which passing through the impulsive noise channel, and then the instantaneous characteristics and high order cumulant features of digital modulation signals are extracted as classification feature set, finally, the BP neural network (BPNN) model as a classifier for automatic digital modulation recognition. Besides, based on the elephant herding optimization (EHO) algorithm and quantum computing mechanism, we design a quantum elephant herding algorithm (QEHA) to optimize the initial thresholds and weights of the BPNN, which solves the problem that traditional BPNN is easy into local minimum values and poor robustness. The experimental results prove that the adaptive weight myriad filter we used can remove the impulsive noise effectively, and the proposed QEHA-BPNN classifier has better recognition performance than other conventional pattern recognition classifiers. Compared with other global optimization algorithms, the QEHA designed in this paper has a faster convergence speed and higher convergence accuracy. Furthermore, the effect of symbol shape has been considered, which can satisfy the need for engineering.

• 한국군사과학기술학회지
• /
• 제25권3호
• /
• pp.219-230
• /
• 2022

In implementing a robust automatic target recognition(ATR) system with synthetic aperture radar(SAR) imagery, one of the most important issues is accurate classification of target variants, which are the same targets with different serial numbers, configurations and versions, etc. In this paper, a deep learning network with channel attention modules is proposed to cope with the recognition problem for target variants based on the previous research findings that the channel attention mechanism selectively emphasizes the useful features for target recognition. Different from other existing attention methods, this paper employs the channel attention modules without dimensionality reduction along the channel direction from which direct correspondence between feature map channels can be preserved and the features valuable for recognizing SAR target variants can be effectively derived. Experiments with the public benchmark dataset demonstrate that the proposed scheme is superior to the network with other existing channel attention modules.

• 한국지능시스템학회논문지
• /
• 제21권1호
• /
• pp.86-99
• /
• 2011

사용자의 행동에 따른 의도 인식의 불확실성 때문에 사용자가 동일한 행동을 하더라도 상황에 따라 그 의도는 다르게 해석되며, 불확실성을 최소화함으로써 사용자 의도 인식의 정확성을 향상 시킬 수 있다. 본 논문에서는 사용자 의도 인식을 위한 온톨로지 기반의 새로운 방법을 제안하고, 불확실성을 최소화하는 방법을 제안한다. 제안하는 방법은 사용자 의도에 대한 온톨로지를 생성하고, 사용자 의도간 계층적 구조와 관계를 RuleML과 동적 베이지안 네트워크를 이용해서 정의하며, 온도, 습도, 시각 등의 수집된 센서 데이터와 정의된 RuleML을 통해 사용자 의도 인식을 보다 정확하게 하는 것이다. 로봇의 능동적 계획수립 방법의 성능을 평가하기 위해 시뮬레이터를 개발했고, 밝생 가능한 모든 상황에 대해 의도인식의 정확도를 측정하는 실험을 했으며, 이에 대한 결과를 제시하였다. 실험결과 비교적 높은 수준의 의도인식 정확도를 나타냈다. 그러나 불확실성을 내재한 행동이 보다 정확한 의도 인식을 방해한다는 것을 알 수 있었다.

• 한국시뮬레이션학회논문지
• /
• 제11권3호
• /
• pp.35-48
• /
• 2002

In the work presented here, we describe a method to extract TrueType features for supporting letter recognition. Even if variously existing document processing techniques have been challenged, almost few methods are capable of recognize a letter associated with its TrueType features supporting OCR free, which boost up fast processing time for image text retrieval. By reviewing the mechanism generating digital fonts and birth of TrueType, we realize that each TrueType is drawn by its contour of the glyph table. Hence, we are capable of deriving the segment with density for a letter with a specific TrueType, defined by the number of occurrence over a segment width. A certain number of occurrence appears frequently often due to the fixed segment width. We utilize letter recognition by comparing TrueType feature library of a letter with that from input word images. Experiments have been carried out to justify robustness of the proposed method showing acceptable results.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2021년도 추계학술발표대회
• /
• pp.1001-1004
• /
• 2021

Pain is an unpleasant experience for the patient. The recognition and assessment of pain help tailor the treatment to the patient, and they are also challenging in the medical. In this paper, we propose an approach for pain recognition through a deep neural network applied to pre-processed physiological. The proposed approach applies the idea of shortcut connections to concatenate the spatial information of a convolutional neural network and the temporal information of a recurrent neural network. In addition, our proposed approach applies the attention mechanism and achieves competitive performance on the BioVid Heat Pain dataset.

• 인지과학
• /
• 제25권1호
• /
• pp.1-24
• /
• 2014

단어내의 글자들을 교환하여 제시할 경우 원래의 단어로 혼동하는 현상인 글자 교환 효과에 대한 연구가 활발하다. 이는 글자교환 효과에 대한 연구가 시각단어 재인시 글자가 어떻게 부호화 되는지와 단어재인 초기과정에 영향을 주는 변인과 처리과정에 대한 정보를 제공하기 때문이다. 본 소고에서는 글자교환 효과에 대한 기존의 설명 모형들을 살펴보고, 하향적 인지적 처리를 반영하는 모형의 필요성을 논의하였다. 특히 한글 처리의 경우, 글자의 위치가 정해져 있지 않고 유동적이라고 보는 기존의 모델들과 달리 하향식으로 글자의 위치가 어휘 하위 단위인 초성, 중성, 종성으로 지정되어 있다는 가정이 필요하다. 따라서 이에 기반한 모형을 탐색하고 추후 연구방향을 논의하였다.

• Journal of Multimedia Information System
• /
• 제7권4호
• /
• pp.239-248
• /
• 2020

The performance of the facial recognition system is determined by many technical factors. Further, most of the technical factors have been realized or are still in continued research. The recognition rate has a great influence on performance not only by technical factors but also by other factors. However, researchers are trying to improve the recognition rate by focusing only on technical factors. The mechanism of recognizing is to compare a face image obtained by photography to an already stored face image and determine the score of the similarity. However, if the photographed image is damaged by external light, even a system with a good algorithm will fail to recognize it. Therefore, it is important to prevent the disturbance of light entering from the outside, so it should be blocked, but the camera will not work without light. Thus, it is proposed that a method to secure the external light but block the disturbance of light that affects photography. A method of blocking disturbance light is to use a polarization filter. There are three polarization methods: circular polarization, linear polarization, and elliptical polarization. In this paper, an experiment was performed to overcome disturbance of light using only a circularly polarized filter. In addition, a lighting system that reproduces disturbance light was provided for the experiment, and light of varying intensities and angles was installed to affect the face recognition camera. As a result of actual application, it was determined that a very improved recognition performance in various disturbance light environments.