• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.12
• /
• pp.2364-2375
• /
• 1994

For the efficient recognition of printed Korean characters, a multiplexed minimum average correlation energy(MMACE) filter is proposed. Proposed method solved the disadvantages of the tree structure algorithm which recognition system is very huge and recognition method is sophisticated. Using only one consonant MMACE filter and one vowel one, we recognized the full Korean character. Each MMACE filter is multiplexed by 4 K-tuple MACE filters which are synthesized by 24 consonants and vowels. Hence the proposed MMACE filter and the correlation distribution plane are divided by 4 subregion. We obtained the binary codes for the Korean character recognition from each correlation distribution subplane. And the obtained codes are compared with the truth table for consonants and vowels in computer. We can recognize the full Korean characters when substitute the corresponded consonant or vowel font of the consistent code to the correlation peak place in the output correlation plane. The computer simulation and optical experiment results show that the proposed compact Korean character recognition system using the MMACE filters has high discrimination capability.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.1
• /
• pp.27-33
• /
• 2020

Recently, visual object detection and tracking has become a vital role in many different applications. It spans various applications like robotics, video surveillance, and intelligent vehicle navigation. Especially, in current situation where the use of UAVs is expanding widely, detection and tracking to soot down illegal UAVs flying over the sky at airports, nuclear power plants and core facilities is becoming a very important task. The remarkable method in object tracking is correlation filter based tracker like KCF (Kernelized Correlation Filter). But it has problems related to target drift in tracking process for long-term tracking. To mitigate the target drift problem in video surveillance application, we propose a tracking method which uses KCF, adaptive thresholding and Kalman filter. In the experiment, the proposed method was verified by using monochrome video sequences which were obtained in the operational environment of UAV.

• Journal of Korea Society of Industrial Information Systems
• /
• v.9 no.2
• /
• pp.81-88
• /
• 2004

For scale and rotation invariant pattern recognition of images with noise, an optical wavelet CHF-fSDF filter is proposed. Wavelet CHF-fSDF filter is synthesized by each single CHF extracted from scale-changed and wavelet transformed images for a referene image as training images. The proposed optical wavelet CHF-fSDF filter is the type of the matched filter so that it can use the structure of 4f optical correlation system. The results of computer simulation show that the proposed filter has the rotation and scale-invariant correlation output and it is useful in the noisy input.

• Journal of Internet Computing and Services
• /
• v.7 no.3
• /
• pp.71-82
• /
• 2006

This paper propose a realtime tracking algorithm of mobile object in indoor environment. this proposed system selects location data closer to mobile objects in real time that are results of Triangulation method and DCM(Database Correlation Method)method. Also, this system applies adjusted location data selected by using Kalman filter, and in result it improved location accuracy of transfer object. Be studied in existing the Kalman filter have unstable location data until its settlement because of it extracts current values by using the past the information. However, proposed location tracking system don't apply existent Kalman filter to this system and it permits precisional tracking location by uses more effective methods.

• Journal of IKEEE
• /
• v.22 no.3
• /
• pp.810-815
• /
• 2018

The kernelized correlation filter algorithm yielded meaningful results in accuracy for object tracking. However, because of the use of a fixed size template, we could not cope with the scale change of the tracking object. In this paper, we propose a method to track objects by finding the best scale for each frame using correlation filtering response values in multi-scale using nearest neighbor interpolation and Gaussian normalization. The scale values of the next frame are updated using the optimal scale value of the previous frame and the optimal scale value of the next frame is found again. For the accuracy comparison, the validity of the proposed method is verified by using the VOT2014 data used in the existing kernelized correlation filter algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.7
• /
• pp.1369-1375
• /
• 2016

In this paper, we present a depth extraction method of integral imaging using correlation between elemental images with phase only filter. Integral imaging is a passive three-dimensional (3D) imaging system records ray information of 3D objects through lenslet array by 2D image sensor, and displays 3D images by using the similar lenslet array. 2D images by lenslet array have different perspectives. These images are referred to as elemental images. Since the correlation can be calculated between elemental images, the depth information of 3D objects can be extracted. To obtain high correaltion between elemental images effectively, in this paper, we use phase only filter. Using this high correlation, the corresponding pixels between elemental images can be found so that depth information can be extracted by computational reconstruction technique. In this paper, to prove our method, we carry out optical experiment and calculate Peak Sidelobe Ratio (PSR) as a correlation metric.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.12
• /
• pp.55-61
• /
• 2017

In this paper, we propose a novel tracking method using target separation and detection that are based on discriminative correlation filter (DCF), which is studied a lot recently. 'Retainability' is one of the most important factor of tracking. There are some factors making retainability of tracking worse. Especially, fast movement and occlusion of a target frequently occur in image data, and when it happens, it would make target lost. As a result, the tracking cannot be retained. For maintaining a robust tracking, in this paper, separation of a target is used so that normal tracking is maintained even though some part of a target is occluded. The detection algorithm is executed and find new location of the target when the target gets out of tracking range due to occlusion of whole part of a target or fast movement speed of a target. A variety of experiments with various image data sets are conducted. The algorithm proposed in this paper showed better performance than other conventional algorithms when fast movement and occlusion of a target occur.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.7
• /
• pp.47-54
• /
• 2017

Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2019.06a
• /
• pp.89-91
• /
• 2019

객체 추적 기술은 컴퓨터 비전 분야에서 활발하게 연구되고 있는 분야로, 인간-컴퓨터 상호작용(HCI)이나 로보틱스, 그리고 자율주행 자동차와 같은 곳에 유용하게 사용될 수 있다. 그중에서도 열화상 객체 추적 기술은 빛이 전혀 없는 어두운 밤에도 적용 가능하기 때문에, 감시 시스템이나 사고 현장의 구조 상황, 또는 군사적 응용에 더욱 유용하다. 그러나 일반적으로 열화상 영상은 컬러 영상보다 해상도가 낮고, 객체의 경계가 흐릿하며, 텍스쳐가 거의 없다는 점 때문에 기존 추적 방법들의 성능 저하의 원인이 된다. 이에 본 논문은 기존 Correlation Filter 기반 추적기에 객체성 특징을 함께 이용하여, 열화상 영상에서의 객체 추적 성능을 향상 시키는 방법을 제안하였다. 또한 실험을 통해 기존 방법보다 열화상 영상에서의 객체 추적 성능이 향상된 것을 보였다.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.4 no.1
• /
• pp.50-56
• /
• 1999

This paper presents consideration on validity of instantaneous correlation power theory. The proposed power theory is defined and analyzed by time domain approach, thus it is easy to understand and instrument. The power is decomposed into active, fundamental reactive and harmonics components based on the autocorrelation and crosscorrelation signal techniques between voltage and current waveforms. On the compensation property, active power filter deal with three components only. Also, for real time control of active power filter, the power models with difficult concept are not cost effective. To verify the validity of the instantaneous correlation power theory, experimental work for voltage type DSP based active power filter is achieved. The power of thyristor controlled motor drives is decomposed into three orthogonal components by proposed power theory. From compensation results, validity of proposed theory is confirmed. feedback controller needs the information on some motor parameters. New recursive adaptation algorithms for rotor resistance and mutual inductance which can be applied to our nonlinear feedback controller are also presented in this paper. The recursive adaptation algorithms make the estimated values of rotor resistance and mutual inductance track their real values. Some simulation and experimental results show that the adaptation algorithms are robust against the variation of stator resistance and stator inductance.