• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.24 no.3
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• pp.321-330
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• 2020

Data classification and clustering is one of the most common applications of the machine learning. In this paper, we aim to provide the insight of the classification for Turing pattern image, which has high nonlinearity, with feature engineering using the machine learning without a multi-layered algorithm. For a given image data X whose fixel values are defined in [-1, 1], X - X³ and ∇X would be more meaningful feature than X to represent the interface and bulk region for a complex pattern image data. Therefore, we use X - X³ and ∇X in the neural network and clustering algorithm to classification. The results validate the feasibility of the proposed approach.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.72-81
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• 2022

Visual Object Tracking is known as the most fundamental problem in the field of computer vision. Object tracking localize the region of target object with bounding box in the video. In this paper, a custom CNN is created to extract object feature that has strong and various information. This network was constructed as a Siamese network for use as a feature extractor. The input images are passed convolution block composed of a bottleneck layers, and features are emphasized. The feature map of the target object and the search area, extracted from the Siamese network, was input as a local proposal network. Estimate the object area using the feature map. The performance of the tracking algorithm was evaluated using the OTB2013 dataset. Success Plot and Precision Plot were used as evaluation matrix. As a result of the experiment, 0.611 in Success Plot and 0.831 in Precision Plot were achieved.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.3289-3298
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• 2011

The region trunk line railroad route considering regional characters is the final aim of railroad management to operators and passengers. For reflecting these aspect to make policies, The study has been performed by defining and analyzing the informations. According to the methodological and political research, First of all, The feature for demand and supply of railroad in the region trunk line railroad route is that demand aspect was excessively influenced by supply aspect. The demand sensitivity was measured very high on the supply changes. The survey, Containing the regional characters, result the railway and bus use patterns are clearly different and this feature is simiral to that of janghang and pohang district. also, In railroad case, Demand shifts from railroad to other transport sensitively. Therefore, We make some new index besides existing index, which like to management index, rate of boarding, rate of using. After that, We suggest passengers and operator's win-win alternatives.

• ETRI Journal
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• v.23 no.4
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• pp.190-198
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• 2001

The performance of Motion Compensated Discrete Cosine Transform (MC-DCT) video coding is improved by using the region adaptive subband image coding [18]. On the assumption that the video is acquired from the camera on a moving platform and the distance between the camera and the scene is large enough, both the motion of camera and the motion of moving objects in a frame are compensated. For the compensation of camera motion, a feature matching algorithm is employed. Several feature points extracted using a Sobel operator are used to compensate the camera motion of translation, rotation, and zoom. The illumination change between frames is also compensated. Motion compensated frame differences are divided into three regions called stationary background, moving objects, and newly emerging areas each of which is arbitrarily shaped. Different quantizers are used for different regions. Compared to the conventional MC-DCT video coding using block matching algorithm, our video coding scheme shows about 1.0-dB improvements on average for the experimental video samples.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.420-427
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• 2017

This paper proposes a new method using Wide Line Detector based statistical shape Feature (WLDF) to identify whether or not a tongue is cracked; a cracked tongue is one of the most frequently used visible features for diagnosis in traditional Chinese Medicine (TCM). We first detected a wide line in the tongue image, and then extracted WLDF, such as the maximum length of each detected region, and the ratio between maximum length and the area of the detected region. We trained a binary support vector machine (SVM) based on the WLDF to build a classifier for cracked tongues. We conducted an experiment based on our proposed scheme, using 196 samples of cracked tongues and 245 samples of non-cracked tongues. The results of the experiment indicate that the recognition accuracy of the proposed method is greater than 95%. In addition, we provide an analysis of the results of this experiment with different parameters, demonstrating the feasibility and effectiveness of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.80-83
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• 2005

A binocular robot vision system having an autonomously moving active viewpoint is proposed. By using this active viewpoint, the system constructs a correspondence between the images of a feature points on the right and left retinas and calculates the spatial coordinates of the feature points. The system incorporates a function of detecting straight lines in an image. To detect lines the system uses Hough transform. The system searches a region surrounded by 4 straight lines. Then the system recognizes the region as a quadrangle. The system constructs a correspondence between the quadrangles in the right and left images. By the use of the result of the constructed correspondence, the system calculates the spatial coordinates of an object. An experiment shows the effect of the line detection using Hough transform, the recognition of the surface of the object and the calculation of the spatial coordinates of the object.

• Speech Sciences
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• v.12 no.2
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• pp.171-182
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• 2005

An efficient GMM (Gaussian mixture modeling) method based on LPCA (local principal component analysis) with VQ (vector quantization) for speaker identification is proposed. To reduce the dimension and correlation of the feature vector, this paper proposes a speaker identification method based on principal component analysis. The proposed method firstly partitions the data space into several disjoint regions by VQ, and then performs PCA in each region. Finally, the GMM for the speaker is obtained from the transformed feature vectors in each region. Compared to the conventional GMM method with diagonal covariance matrix, the proposed method requires less storage and complexity while maintaining the same performance requires less storage and shows faster results.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.138-144
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• 2010

This paper presents the experimental analysis of a F-Hessian SIFT-Based Railroad Level-Crossing Safety Vision System. Region of surveillance, region of interests, data matching based on extracting feature points has been examined under the laboratory condition by the model rig on a small scale. Real-time system were observed by using SIFT based on F-Hessian feature tracking method and other common algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.465-472
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• 2015

This paper presents a visual touch recognition for NUI(Natural User Interface) using Voronoi-tessellation algorithm. The proposed algorithms are three parts as follows: hand region extraction, hand feature point extraction, visual-touch recognition. To improve the robustness of hand region extraction, we propose RGB/HSI color model, Canny edge detection algorithm, and use of spatial frequency information. In addition, to improve the accuracy of the recognition of hand feature point extraction, we propose the use of Douglas Peucker algorithm, Also, to recognize the visual touch, we propose the use of the Voronoi-tessellation algorithm. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.787-795
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• 2008

Human recognition on camera is an interesting topic in computer vision. While fingerprint and face recognition have been become common, gait is considered as a new biometric feature for distance recognition. In this paper, we propose a gait recognition algorithm based on the knee angle, 2 feet distance, walking velocity and head direction of a person who appear in camera view on one gait cycle. The background subtraction method firstly use for binary moving object extraction and then base on it we continue detect the leg region, head region and get gait features (leg angle, leg swing amplitude). Another feature, walking speed, also can be detected after a gait cycle finished. And then, we compute the errors between calculated features and stored features for recognition. This method gives good results when we performed testing using indoor and outdoor landscape in both lateral, oblique view.