• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.191-197
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• 2015

In this paper, we propose the system which recognize the gaze using Random Forests in vehicular environment based on smart-phone. Proposed system is mainly composed of the following: face detection using Adaboost, face component estimation using Histograms, and gaze recognition based on Random Forests. We detect a driver based on the image information with a smart-phone camera, and the face component of driver is estimated. Next, we extract the feature vectors from the estimated face component and recognize gaze direction using Random Forest recognition algorithm. Also, we collected gaze database including a variety gaze direction in real environments for the experiment. In the experiment result, the face detection rate and the gaze recognition rate showed 82.02% and 84.77% average accuracies, respectively.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.145-152
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• 2002

As the number of digital images available to users is exponentially growing due to the rapid development of digital technology, content-based image retrieval (CBIR) has been one of the most active research areas. A variety of image retrieval methods have been proposed, where, given an input query image, the images that are similar to the input are retrieved from an image database based on low-level features such as colors and textures. However, most of the existing retrieval methods did not consider the case when an input query image is a part of a whole image in the database due to the high complexity involved in partial matching. In this paper, we present an efficient method for partial image matching by using the histogram distribution relationships between query image and whole image. The proposed approach consists of two steps: the first step prunes the search space and the second step performs block-based retrieval using partial image matching to rank images in candidate set. The experimental results demonstrate the feasibility of the proposed algorithm after assuming that the response tune of the system is very high while retrieving only by using partial image matching without Pruning the search space.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.306-310
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• 2002

In this paper, we realized a system that converts the Korean alphabet (Hangul) images, which are in any domain that is formed by the finger movement on the Hangul document, to the editable characters and then outputs them to the word editor. The domain of hand is separated from the sphere of document in the pre-process step of image. The centroid point of hand is drawn by the maximum circular movement method. After the system recognizes the hand with the circular pattern vector algorithm, finds out the position of finger by the distance spectrum and then draws out the sphere of selected character image by the finger movement to divide the characters into character units by applying the histogram between the Hangul characters. We standardized the characters of various sizes. We used the circular pattern vector algorithm that grafts on the fuzzy inference to divert the character images of the domain, which user wants, to the editable characters by comparing the characteristic vectors between the standard pattern character and the inputted character and by recognizing the character.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.923-932
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• 2017

In this paper, we propose a GRNN(: Generalized Regression Neural Network) algorithms for new eyes and face recognition identification system to solve the points that need corrective action in accordance with the existing problems of facial movements gaze upon it difficult to identify the user and. Using a Kalman filter structural information elements of a face feature to determine the authenticity of the face was estimated future location using the location information of the current head and the treatment time is relatively fast horizontal and vertical elements of the face using a histogram analysis the detected. And the light obtained by configuring the infrared illuminator pupil effects in real-time detection of the pupil, the pupil tracking was to extract the text print vector. The abstract is to be in fully-justified italicized text as it is here, below the author information.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.82-88
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• 2002

In this paper, we proposed a audio indexing method that is used wavelet transform for audio data retrieval. It is difficult for audio data to make a efficient audio data index because of its own particular properties, such as requirement of large storage, real time to transfer and wide bandwidth. An audio data in del using wavelet transform make it possible to index and retrieval by using the particular wavelet transform properties. Our proposed indexing method doesn't separate data to several blocks. Therefore we use both high-pass and low-pass parts of last level coefficient of wavelet transform. Audio data indexing is made by applying the string matching algorithm to high-pass part and zero-crossing histogram to low-pass part. These are transformed to the continued strings, Through this method, we described a retrieval efficiency. The retrieval method is done by comparing the database index string to the query string and then data of minimum values is chosen to the result. Our simulation decided proper comparative coefficient and made known changing of retrieval efficiency versus audio data length. The results show that the proposed method improves retrieval efficiency compared to conventional method.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.749-757
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• 2001

We present a simple artificial landmark model and robust landmark tracking algorithm for mobile robot localization. The landmark model, consisting of symmetric and repetitive color patches, produces color histograms that are invariant under the geometric and photometric distortions. A stochastic approach based on the CONDENSATION tracks the landmark model robustly even under the varying illumination conditions. After the landmark detection, relative position of the mobile robot to the landmark is calculated. Experimental results show that the proposed landmark model is effective and can be detected and tracked in a clustered scene robustly. With the tracked single landmark, we extract geometrical information than achieve accurate localization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.652-657
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• 2015

BitTorrent is an innovative protocol related to file-sharing and file-transferring, which allows users to receive pieces of files from multiple sharer on the Internet to make the pieces into complete files. In reality, however, free distribution of illegal or copyright related video data is counted for crime. Difficulty of regulation on the copyright of data on BitTorrent is caused by the fact that data is transferred with the pieces of files instead of the complete file formats. Therefore, the classification process of file formats of the digital contents should take precedence in order to restore digital contents from the pieces of files received from BitTorrent, and to check the violation of copyright. This study has suggested SVM classifier for the classification of digital files, which has the feature vector of histogram differential on the pieces of files. The suggested classifier has evaluated the performance with the division factor by applying the classifier to three different formats of video files.

• Journal of Broadcast Engineering
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• v.10 no.4 s.29
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• pp.576-586
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• 2005

This paper presents a new estimation and representation of a disparity map for stereo-based video communication systems. Several pixel-based and block-based algorithms have been proposed to estimate the disparity map. While the pixel-based algorithms can achieve high accuracy in computing the disparity map, they require a lost of bits to represent the disparity information. The bit rate can be reduced by the block-based algorithm, sacrificing the representation accuracy. In this paper, the block enclosing a distinct edge is divided into two regions and the disparity of each region is set to that of a neighboring block. The proposed algorithm employs accumulated histograms and a neural network to classify a type of a block. In this paper, we proved that the proposed algorithm is more effective than the conventional algorithms in estimating and representing disparity maps through several experiments.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.379-387
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• 2001

We proposed an enhanced extraction method of vehicle plate, in which both the brightness variation of gray and the Hue value of HSI color model were used. For the extraction of the vehicle plate from a vehicle image, first of all, candidate regions for the vehicle plate were extracted from the image by using the property of brightness variation of the image. A real place region was determined among candidate regions by the density of pixels with the Hue value of green and white. For- extracting the feature area containing characters from the extracted vehicle plate, we used the histogram-based approach of individual characters. And we proposed and applied for the recognition of characters the enhanced ART2 algorithm which support the dynamical establishment of the vigilance threshold with the genera]iced union operator of Yager. In addition, we propose an enhanced SOSL algorithm which is integrated both enhanced ART2 and supervised learning methods. The performance evaluation was performed using 100's real vehicle images and the evaluation results demonstrated that the extraction rates of tole proposed extraction method were improved, compared with that of previous methods based un brightness variation, RGB and HSI individually . Furthermore, the recognition rates of the proposed algorithms were improved much more than that of the conventional ART2 and BP algorithms.