• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.493-504
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• 2010

This study proposes a classification method based on an automated training extraction procedure that may be used with very high resolution (VHR) images of non-accessible areas. The proposed method overcomes the problem of scale difference between VHR images and geographic information system (GIS) data through filtering and use of a Landsat image. In order to automate maximum likelihood classification (MLC), GIS data were used as an input to the MLC of a Landsat image, and a binary edge and a normalized difference vegetation index (NDVI) were used to increase the purity of the training samples. We identified the thresholds of an NDVI and binary edge appropriate to obtain pure samples of each class. The proposed method was then applied to QuickBird and SPOT-5 images. In order to validate the method, visual interpretation and quantitative assessment of the results were compared with products of a manual method. The results showed that the proposed method could classify VHR images and efficiently update GIS data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.350-353
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• 2013

In this paper, a hardware implementation of phase calculator for extracting 3D depth image from TOF(Time-Of-Flight) sensor is proposed. The designed phase calculator, which adopts redundant binary number systems and a pipelined architecture to improve throughput and speed, performs arctangent operation using vectoring mode of DCORDIC algorithm. Fixed-point MATLAB simulations are carried out to determine the optimized bit-widths and number of iteration. The designed phase calculator is verified by emulating the restoration of virtual 3D data using MATLAB/Simulink and FPGA-in-the-loop verification, and the estimated performance is about 7.5 Gbps at 469 MHz clock frequency.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.767-773
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• 2008

This paper presents a localization system based on the use of electric compass and tracking IR light source. Digital RGB(Red, Green, Blue)signal of digital CMOS Camera is sent to CPLD which converts the color image to binary image at 30 frames per second. CMOS camera has IR filter and UV filter in front of CMOS cell. The filters cut off above 720nm light source. Binary output data of CPLD is sent to DSP that rapidly tracks the IR light source by moving Camera tilt DC motor. At a robot toward north, electric compass signals and IR light source angles which are used for calculating the data of the location system. Because geomagnetic field is linear in local position, this location system is possible. Finally, it is shown that position error is within ${\pm}1.3cm$ in this system.

• ETRI Journal
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• v.43 no.6
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• pp.1113-1129
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• 2021

Lightweight ciphers are increasingly employed in cryptography because of the high demand for secure data transmission in wireless sensor network, embedded devices, and Internet of Things. The PRESENT algorithm as an ultralightweight block cipher provides better solution for secure hardware cryptography with low power consumption and minimum resource. This study generates the key using key rotation and substitution method, which contains key rotation, key switching, and binary-coded decimal-based key generation used in image encryption. The key rotation and substitution-based PRESENT architecture is proposed to increase security level for data stream and randomness in cipher through providing high resistance to attacks. Lookup table is used to design the key scheduling module, thus reducing the area of architecture. Field-programmable gate array (FPGA) performances are evaluated for the proposed and conventional methods. In Virtex 6 device, the proposed key rotation and substitution PRESENT architecture occupied 72 lookup tables, 65 flip flops, and 35 slices which are comparably less to the existing architecture.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2365-2373
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• 2011

This paper propose the hardware IP of real-time face detection system for mobile devices and digital cameras required for high speed, smaller size and lower power. The proposed face detection system is robust against illumination changes, face size, and various face angles as the main cause of the face detection performance. Input image is transformed to LBP(Local Binary Pattern) image to obtain face characteristics robust against illumination changes, and detected the face using face feature data that was adopted to learn and generate in the various face angles using the Adaboost algorithm. The proposed face detection system can be detected maximum 36 faces at the input image size of QVGA($320{\times}240$), and designed by Verilog-HDL. Also, it was verified hardware implementation by using Virtex5 XC5VLX330 FPGA board and HD CMOS image sensor(CIS) for FPGA verification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.198-205
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• 2016

In the contemporary world, the breakthrough of the ultra-modern technologies has been blessed with the camera. This device has become omnipresent either integrated on with other devices such as smartphones, notebooks, laptops, handheld devices and so on. In addition, digital signage, display and monitors have also become very widespread around us everywhere. These types of scenarios have made imaginable to imagine about the consuming of the unused resources. The dual use of displayed contents can make it possible to use it as an advertisement as well as a transmitter for camera based communication. In this study, a digital watermarking algorithm based communication method has been analyzed. We have introduced Binary Pattern (BP) based a new message extracting algorithm to extract message in an efficient way from the watermarked image compared to other algorithms. Besides, the previous works using camera and display have been illustrated using comparative analysis. This paper has demonstrated an advantageous overview using the experimental results which reveals that the proposed methodology significantly reduces the complexity while augmenting the advantages of the proposed scheme. Moreover, the simulation results have shown the advantages of the proposed scheme over the other schemes.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.275-280
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• 1990

A neural network method is applied for recognizing the orientation o f individual parts being fed from a bowl feeder. The system is designed in such a way that a part can be discriminated and sorting according to every possible stable orientation without implementing any a mechanical tooling. The operation of the bowl feeder is based on a 2D image obtained from an array of fiber optic sensor located on the feeder track. The acquired binary image of a moving and vibrating part is used as input to a neural network which, in turn, determines t he orientation of the part. The main task of the neural network, here is to synthesize the appropriate internal discriminant functions for the part orientation using the part features. A series of the experiments reveals several promising points on performance. Since the operation of the feeder is highly programmable, it is well suited for feeding and sorting small parts prior to small batch assembly work.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.289-292
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• 2007

An object color identification and classification embedded system realization for uninhabited stock management is presented in this paper. The embedded system is realized by using ultrasonic sensor to extract the object and distance, and detecting binary image from USB CCD camera. The algorithm is identified by comparing the reference pattern with the color pattern of input image, and move to the settled rack at the store. The experimental result leads to use the uninhibited stock management with practice as a robot.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.216-220
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• 2018

In this paper, we present visual sensing techniques that can be used to teach a robot using a laser pointer. The light spot of an off-the-shelf laser pointer is detected and its movement is tracked on consecutive images of a camera. The three-dimensional position of the spot is calculated using stereo cameras. The light spot on the image is detected based on its color, brightness, and shape. The detection results in a binary image, and morphological processing steps are performed on the image to refine the detection. The movement of the laser spot is measured using two methods. The first is a simple method of specifying the region of interest (ROI) centered at the current location of the light spot and finding the spot within the ROI on the next image. It is assumed that the movement of the spot is not large on two consecutive images. The second method is using a Kalman filter, which has been widely employed in trajectory estimation problems. In our simulation study of various cases, Kalman filtering shows better results mostly. However, there is a problem of fitting the system model of the filter to the pattern of the spot movement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.643-650
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• 2014

A hardware implementation of phase calculator for extracting 3D depth image from TOF(Time-Of-Flight) sensor is described. The designed phase calculator adopts redundant binary number systems and a pipelined architecture to improve throughput and speed. It performs arctangent operation using vectoring mode of DCORDIC(Differential COordinate Rotation DIgital Computer) algorithm. Fixed-point MATLAB simulations are carried out to determine the optimal bit-widths and number of iteration. The phase calculator has ben verified by FPGA-in-the-loop verification using MATLAB/Simulink. A test chip has been fabricated using a TSMC $0.18-{\mu}m$ CMOS process, and test results show that the chip functions correctly. It has 82,000 gates and the estimated throughput is 400 MS/s at 400Mhz@1.8V.