• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.223-226
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• 1995

New output voltage control technique based on the simple feedback linearization is proposed. The system states are first divided into fast states and slow states. Then, the control stage is composed of the fast inner current control loop and the slow outer voltage control loop. From the inner loop, the average control is derived by the sliding mode concept and it is inserted into the dynamic equations of the slow states in the outer loop. Applying the feedback linearization technique to the obtained large-signal models of the PWM dc-dc converters, linearized large-signal models are obtained for the slow states. With this technique, the output voltage controller of the PWM dc-dc converters can be designed easily in the global state space and its control performance can also be much improved.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.8
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• pp.855-861
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• 2007

Haptic rendering is a process providing force feedback during interactions between a user and a virtual object. This paper presents a real-time haptic rendering technique for deformable objects based on visual information of intervention between a tool and a real object in a remote place. A user can feel the artificial reaction force through a haptic device in real-time when a slave system exerts manipulation tasks on a deformable object. The models of the deformable object and the manipulator are created from the captured image obtained with a CCD camera and the recognition of objects is achieved using image processing techniques. The force at a rate of 1 kHz for stable haptic interaction is deduced using extrapolation of forces at a low update rate. The rendering algorithm developed was tested and validated on a test platform consisting of a one-dimensional indentation device and an off-the shelf force feedback device. This software system can be used in a cellular manipulation system providing artificial force feedback to enhance a success rate of operations.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.141-152
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• 2005

A new emotion-based image retrieval method is proposed in this paper. Query emotion descriptors called query color code and query gray code are designed based on the human evaluation on 13 emotions('like', 'beautiful', 'natural', 'dynamic', 'warm', 'gay', 'cheerful', 'unstable', 'light' 'strong', 'gaudy' 'hard', 'heavy') when 30 random patterns with different color, intensity, and dot sizes are presented. For emotion image retrieval, once a query emotion is selected, associated query color code and query gray code are selected. Next, DB color code and DB gray code that capture color and, intensify and dot size are extracted in each database image and a matching process between two color codes and between two gray codes are peformed to retrieve relevant emotion images. Also, a new relevance feedback method is proposed. The method incorporates human intention in the retrieval process by dynamically updating weights of the query and DB color codes and weights of an intra query color code. For the experiments over 450 images, the number of positive images was higher than that of negative images at the initial query and increased according to the relevance feedback.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.107.6-107
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• 2002

$\textbullet$ An autonomous mobile robot was controlled through the Internet. $\textbullet$ For the direct control, the feedback data should be provided properly. $\textbullet$ Therefore, an efficient communication scheme should be defined. $\textbullet$ To overcome the transmission delay, the highly abstracted message format was used. $\textbullet$ As the feedback data, the real image sequences may suffer the transmission delay or loss of content. $\textbullet$ To resolve this, the feature information was used to construct the synthetic feedback information. $\textbullet$ By doing this, the operator could feel the hands-on control with an Internet-based robot.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.61-69
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• 1994

For distortion-invariant recognition of Korean characters, a holographic implementation of an optical associative memory system is proposed. The structure of the proposed system is a single-layer neural network employing interconneclion matrix, thresholding and feedback. To provide the interconnection matrix, we use two CGII's which are placed on intermcdiate plane of cascaded Vander Lugt corrclators to form an optical memory loop. The holographic correlator stores reference images in a hologram and retrives them in a coherently illuminated feedback loop. An input image which maybe noisy or incomplete, is applicd to the system and simultaneously correlated optically with all of the stord images. These correlations are throsholed and fed back to the input, where the strongest correlation reinforces the input image. The enhanced image passes arround the loop repeatedly, approaching the stored image more closely on each pass until the system stabilizes on the desired image. The computer simulation results show that the proposed Korean Character recognition algorithm has high discrimination capability and noise immunity.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.89-96
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• 2000

Relevance feedback is a technique to learn the user's subjective perception of similarity between images, and has recently gained attention in Content Based Image Retrieval. Most relevance feedback methods assume that the individual features that are used in similarity judgments do not interact with each other. However, this assumption severely limits the types of similarity judgments that can be modeled In this paper, we explore a more sophisticated model for similarity judgments based on fuzzy measures and the Choquet Integral, and propose a suitable algorithm for relevance feedback, Experimental results show that the proposed method is preferable to traditional weighted- average techniques.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.585-592
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• 2013

CBIR is an effective tool to search and extract image contents in a large remote sensing image database queried by an operator or end user. However, as imaging principles are different by sensors, their visual representation thus varies among image modality type. Considering images of various modalities archived in the database, image modality difference has to be tackled for the successful CBIR implementation. However, this topic has been seldom dealt with and thus still poses a practical challenge. This study suggests a cross modality CBIR (termed as the CM-CBIR) method that transforms given query feature vector by a supervised procedure in order to link between modalities. This procedure leverages the skill of analyst in training steps after which the transformed query vector is created for the use of searching in target images with different modalities. Current initial results show the potential of the proposed CM-CBIR method by delivering the image content of interest from different modality images. Despite its retrieval capability is outperformed by that of same modality CBIR (abbreviated as the SM-CBIR), the lack of retrieval performance can be compensated by employing the user's relevancy feedback, a conventional technique for retrieval enhancement.

• Journal of Information Processing Systems
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• v.9 no.3
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• pp.349-364
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• 2013

The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.669-672
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• 2001

We propose an efficient algorithm for an interactive content-based image retrieval using relevance feedback. In the proposed algorithm, a new query feature vector first is yielded from the average feature vector of the relevant images that is fed back from the result images of the previous retrieval. Each component weight of a feature vector is computed from an inverse of standard deviation for each component of the relevant images. The updated feature vector of the query and the component weights are used in the iterative retrieval process. In addition, the irrelevant images are excluded from object images in the next iteration to obtain additional performance improvement. In order to evaluate the retrieval performance of the proposed method, we experiment for three image databases, that is, Corel, Vistex, and Ultra databases. We have chosen wavelet moments, BDIP and BVLC, and MFS as features representing the visual content of an image. The experimental results show that the proposed method yields large precision improvement.

• Journal of Sensor Science and Technology
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• v.24 no.2
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• pp.131-136
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• 2015

This paper presents a wide dynamic range complementary metal oxide semiconductor (CMOS) image sensor with column capacitor and feedback structure. The designed circuit has been fabricated by using $0.18{\mu}m$ 1-poly 6-metal standard CMOS technology. This sensor has dual mode operation using combination of active pixel sensor (APS) and passive pixel sensor (PPS) structure. The proposed pixel operates in the APS mode for high-sensitivity in normal light intensity, while it operates in the PPS mode for low-sensitivity in high light intensity. The proposed PPS structure is consisted of a conventional PPS with column capacitor and feedback structure. The capacitance of column capacitor is changed by controlling the reference voltage using feedback structure. By using the proposed structure, it is possible to store more electric charge, which results in a wider dynamic range. The simulation and measurement results demonstrate wide dynamic range feature of the proposed PPS.