• The Journal of the Acoustical Society of Korea
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• v.26 no.1
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• pp.25-31
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• 2007

This paper describes an attempt to prevent the external acoustic noise from being misrecognized as the speech recognition target. For this, in the speech activity detection process for the speech recognition, it confirmed besides the acoustic energy to the lip movement image signal of a speaker. First of all, the successive images are obtained through the image camera for PC. The lip movement whether or not is discriminated. And the lip movement image signal data is stored in the shared memory and shares with the recognition process. In the meantime, in the speech activity detection Process which is the preprocess phase of the speech recognition. by conforming data stored in the shared memory the acoustic energy whether or not by the speech of a speaker is verified. The speech recognition processor and the image processor were connected and was experimented successfully. Then, it confirmed to be normal progression to the output of the speech recognition result if faced the image camera and spoke. On the other hand. it confirmed not to output of the speech recognition result if did not face the image camera and spoke. That is, if the lip movement image is not identified although the acoustic energy is inputted. it regards as the acoustic noise.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.300-306
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• 2012

In this paper, we propose a vision based hand motion recognition method for an untouchable user interface of smart devices. First, an original color image is converted into a gray scaled image and its spacial resolution is reduced, taking the small memory and low computational power of smart devices into consideration. For robust recognition of hand motions through separation of horizontal and vertical motions, the horizontal principal area (HPA) and the vertical principal area (VPA) are defined respectively. From the difference images of the consecutively obtained images, the center of gravity (CoG) of the significantly changed pixels caused by hand motions is obtained, and the direction of hand motion is detected by defining the least mean squared line for the CoG in time. For verifying the feasibility of the proposed method, the experiments are carried out with a vision system.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.19-28
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• 2015

With the aim of developing a smartphone-based point-of-care device that is small, inexpensive, and easy to handle by non-expert, we designed a fluorescence smartscope for counting particles and a DC motor-controlled particle positioning system. Our smartscope can count the number of fluorescent particles and fluorescently-stained white blood cells through a phone camera with an adaptor containing a LED, a ball lens and optical filters and an application running on a smartphone. The motor was controlled wirelessly via Bluetooth with an Android smartphone. We found that axial spinning of a helical microfluidic channel allows arrangement of particles having size similar to the white blood cells. The motor-controlled particle positioning system can minimize time-consuming manual processes and automate sample preparation process and thus, if integrated with the smartscope, it can be used for a point-of-care testing device based on a smartphone.

• Journal of KIISE
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• v.44 no.3
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• pp.295-305
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• 2017

Facial appearance is greatly influenced by illumination conditions, and therefore illumination variation is one of the factors that degrades performance of face recognition systems. In this paper, we propose a robust method for face representation under varying illumination conditions, combining non-alpha Weberface (non-alpha WF) and histogram equalization. We propose a two-step method: (1) for a given face image, non-alpha WF, which is not applied a parameter for adjusting the intensity difference between neighboring pixels in WF, is computed; (2) histogram equalization is performed to non-alpha WF, to make a uniform histogram distribution globally and to enhance the contrast. $(2D)^2PCA$ is applied to extract low-dimensional discriminating features from the preprocessed face image. Experimental results on the extended Yale B face database and the CMU PIE face database show that the proposed method yielded better recognition rates than several illumination processing methods as well as the conventional WF, achieving average recognition rates of 93.31% and 97.25%, respectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.1
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• pp.39-47
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• 2017

Nowadays, there have been an increasing number of illegal use cases where people try to fabricate the working hours by using fake fingerprints. So, the fingerprint liveness detection techniques have been actively studied and widely demanded in various applications. This paper proposes a new method to detect fake fingerprints using CNN (Convolutional Neural Ntworks) based on the patches of fingerprint images. Fingerprint image is divided into small square sized patches and each patch is classified as live, fake, or background by the CNN. Finally, the fingerprint image is classified into either live or fake based on the voting result between the numbers of fake and live patches. The proposed method does not need preprocessing steps such as segmentation because it includes the background class in the patch classification. This method shows promising results of 3.06% average classification errors on LivDet2011, LivDet2013 and LivDet2015 dataset.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.229.1-229.1
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• 2015

생체 시료인 세포나 조직을 분석을 위해 임의로 파괴하거나 훼손하지 않은 본래의 상태에서 세포에 존재하는 다양한 생체분자 물질의 질량과 조성을 분석하고 영상화할 수 있는 대기압 표면 질량분석 이미징 기술을 개발했다. 생체 시료의 표면을 질량 분석을 하기 위해서는 대기압 분위기에서 시료에 열적 손상이 없는 조건으로 시편의 이온화 및 탈착 과정이 이루어지게 하기 위해 저온 대기압 탈착/이온화원으로 저온대기압 플라즈마 젯과 펨토초 적외선 레이저를 결합하여 대기압 이온화원을 제작하였다. 기존에 잘 알려진 저온 대기압 플라즈마 젯 소자는 유리관에 방전기체를 흘려주고 전극에 고전압을 인가하는 방식으로 제작했으며, 또 다른 대기압 이온화원으로서 근적외선 대역의 고출력 펨토초 레이저 빔을 현미경용 대물렌즈로 집속하여 생체시료에 조사시켰다. 수백 나노미터에서 수 마이크로미터 수준으로 빔을 집속할 수 있는 펨토초 레이저는 금나노로드의 도움으로 생체 시료를 매우 작은 수준으로 탈착하는 데 주로 사용하며, 수십 마이크로미터에서 수 밀리미터 정도의 크기를 가지는 저온 대기압 플라즈마 젯은 탈착된 물질을 이온화시키는데 사용하여, 이 두 가지 이온화원을 결합하여 이온화원으로 사용한다. 시료에서 발생한 이온을 질량분석기 입구까지 잘 끌고 갈 수 있도록 이온 전달관을 설계하고 보조펌프를 장착 사용한다. 이렇게 자체 개발한 대기압 이온화원을 상용 질량분석기기와 결합하여 대기압 분위기에서 시료의 표면을 질량분석할 수 있는 시스템과 측정 기술을 개발했다. 현미경 스테이지에 정밀 2-D 자동 스캐닝 스테이지를 장착하여 질량분석 정보에 공간 정보를 더할 수 있는 질량분석 이미징 기술 방법을 개발하여 생체 시편의 질량분석 이미징을 얻었다. 수분을 포함하는 생채시료로부터 단백질, 지질, 대사물질을 직접 분리하여 분석하는 이 새로운 질량분석법은 기존의 분석법에 비해 훨씬 더 많은 생체분자 정보를 얻을 수 있으며 공간정보를 더해 영상화할 수 있는 큰 장점이 있다. 대기압 표면 질량분석 기술은 생체시료를 파괴해서 용액화할 필요도 없으며, 진공 챔버에 넣기 위해 필요한 복잡한 전처리 과정 단계를 간략화 할 수 있으며 최종적으로는 살아있는 세포나 생체 조직도 정량 분석이 가능하여 생명과학 및 의료진단 분야에서 응용할 수 있는 분야는 무궁무진할 것이다.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.451-458
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• 2004

A leather quality inspection by naked eyes has known as unreliable because of its biological characteristics like accumulated fatigue caused from an optical illusion and biological phenomenon. Therefore it is necessary to automate the leather quality inspection by computer vision technique. In this paper, we present automatic leather qua1ity classification system get information from leather surface. Leather is usually graded by its information such as texture density, types and distribution of defects. The presented algorithm explain how we analyze leather information like texture density and defects from the gray-level images obtained by digital camera. The density data is computed by its ratio of distribution area, width, and height of Fourier spectrum magnitude. And the defect information of leather surface can be obtained by histogram distribution of pixels which is Windowed from preprocessed images. The information for entire leather could be a standard for grading leather quality. The proposed leather inspection system using machine vision can also be applied to another field to substitute human eye inspection.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.323-331
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• 2005

This paper proposes an improved system for recognizing facial expressions in various internal states that is illumination-invariant and without detectable rue such as a neutral expression. As a preprocessing to extract the facial expression information, a whitening step was applied. The whitening step indicates that the mean of the images is set to zero and the variances are equalized as unit variances, which reduces murk of the variability due to lightening. After the whitening step, we used the facial expression information based on principal component analysis(PCA) representation excluded the first 1 principle component. Therefore, it is possible to extract the features in the lariat expression images without detectable cue of neutral expression from the experimental results, we ran also implement the various and natural facial expression recognition because we perform the facial expression recognition based on dimension model of internal states on the images selected randomly in the various facial expression images corresponding to 83 internal emotional states.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.636-642
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• 2017

In this paper, We proposed a novel hand-gesture recognition algorithm using concentric-circle expanding and tracing. The proposed algorithm determines region of interest of hand image through preprocessing the original image acquired by web-camera and extracts the feature of hand gesture such as the number of stretched fingers, finger tips and finger bases, angle between the fingers which can be used as intuitive method for of human computer interaction. The proposed algorithm also reduces computational complexity compared with raster scan method through referencing only pixels of concentric-circles. The experimental result shows that the 9 hand gestures can be recognized with an average accuracy of 90.7% and an average algorithm execution time is 78ms. The algorithm is confirmed as a feasible way to a useful input method for virtual reality, augmented reality, mixed reality and perceptual interfaces of human computer interaction.

• The KIPS Transactions:PartA
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• v.10A no.4
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• pp.357-368
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• 2003

Evaluation of shape similarity for 3D models is essential in many areas - medicine, mechanical engineering, molecular biology, etc. Moreover, as 3D models are commonly used on the Web, many researches have been made on the classification and retrieval of 3D models. In this paper, we describe methods for 3D shape representation and major concepts of similarity evaluation, and analyze the key features of recent researches for shape comparison after classifying them into four categories including multi-resolution, topology, 2D image, and statistics based methods. In addition, we evaluated the performance of the reviewed methods by the selected criteria such as uniqueness, robustness, invariance, multi-resolution, efficiency, and comparison scope. Multi-resolution based methods have resulted in decreased computation time for comparison and increased preprocessing time. The methods using geometric and topological information were able to compare more various types of models and were robust to partial shape comparison. 2D image based methods incurred overheads in time and space complexity. Statistics based methods allowed for shape comparison without pose-normalization and showed robustness against affine transformations and noise.