• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.131-137
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• 2013

The barrel distortion makes serious problems in a wide-angle camera employing a lens of a short focal length. This paper presents a low-complexity hardware architecture for a real-time barrel distortion corrector and its implementation. In the proposed barrel distortion corrector, the conventional algorithm is modified so that the correction is performed incrementally, which results in the reduction of the number of required hardware modules for the distortion correction. The proposed barrel distortion corrector has a pipelined architecture so as to achieve a high-throughput correction. The correction rate is 74.86 frames per sec at the operating frequency of 314MHz in a $0.11{\mu}m$ CMOS process, where the frame size is $2048{\times}2048$. The proposed barrel distortion corrector is implemented with 14.3K logic gates.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.181-190
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• 2013

We propose an interpolation method considering barrel distortion of fisheye lens using nearest pixels on a corrected image. The correction of barrel distortion comprises coordinate transformation and interpolation. This paper focuses on interpolation. The proposed interpolation method uses nearest four coordinates on a corrected image rather than on a distorted image unlike existing techniques. Experimental results show that both subjective and objective image qualities are improved.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.57-66
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• 2014

This paper presents a low-complexity barrel distortion correction processor for wide-angle cameras. The proposed processor performs the barrel distortion correction jointly with the color demosaicking, so that the hardware complexity can be reduced significantly. In addition, to reduce the required memory bandwidth, an efficient memory interface is proposed by utilizing the spatial locality of the memory access in the correction process. The proposed processor is implemented with 35K logic gates in a $0.11-{\mu}m$ CMOS process and its correction speed is 150 Mpixels/s at the operating frequency of 606MHz, where the supported frame size is $2048{\times}2048$ and the required memory bandwidth is 1 read/cycle.

• Journal of the Semiconductor & Display Technology
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• v.13 no.3
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• pp.57-60
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• 2014

The distortion correction system of Head up display that is installed in vehicle has been studied both experimentally and theoretically for the removal of the optical lens distortion. A new adaptive correction method is having a decisive effect on correction in the optical lens distortion of Head up display. This adaptive correction system removes various distortion that has occurred because of the design tolerances of Head up display and the assemble tolerances into vehicle. It is especially efficient in removal of a barrel distortion and pin cushion of Head up display.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.36-44
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• 2015

This paper proposes a low-complexity processor to correct vignetting and barrel distortion for wide-angle cameras. The proposed processor calculates the required correcting factors by employing the piecewise linear approximation so that the hardware complexity can be reduced significantly while maintaining correction quality. In addition, the processor is designed to correct the two distortions concurrently in a singular pipeline, which reduces the overall complexity. The proposed processor is implemented with 18.6K logic gates in a $0.11{\mu}m$ CMOS process and shows the maximum correction speed of 200Mpixels/s for correcting an image of which size is $2048{\times}2048$.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.49-60
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• 2012

In this paper, we propose a hardware design for correction of barrel distortion using the nearest coordinates in the corrected image. Because it applies the nearest distance on corrected image rather than adjacent distance on distorted image, the picture quality is improved by the image whole area, solve the staircase phenomenon in the exterior area. But, because of additional arithmetic operation using design of bilinear interpolation, required arithmetic operation is increased. Look up table(LUT) structure is proposed in order to solve this, coordinate rotation digital computer(CORDIC) algorithm is applied. The results of the synthesis using Design compiler, the design of implementing all processes of the interpolation method with the hardware is higher than the previous design about the throughput, In case of the rear camera, the design of using LUT and hardware together can reduce the size than the design of implementing all processes with the hardware.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.299-301
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• 1996

Since a standard lens has small sight angle, a fish-eye lens can be used in order to obtain wide sight angle for the robot vision system. In spite of the advantage, the image through the lens has variable resolution; the central information of the lens is of high resolution, but the peripheral information is of low resolution. Owing to this difference of resolution, the variable resolution image should be transformed to a uniform resolution image in order to determine the positions of the objects in the image. In this work, the correction method for the distorted image is presented and the performance is analyzed. Furthermore, the camera with a fish eye lens can be used to determine the real world coordinates. The performance is shown through experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3981-4004
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• 2019

This paper proposes a novel method for locating objects in real space from a single remote image and measuring actual distances between them by automatic detection and perspective transformation. The dimensions of the real space are known in advance. First, the corner points of the interested region are detected from an image using deep learning. Then, based on the corner points, the region of interest (ROI) is extracted and made proportional to real space by applying warp-perspective transformation. Finally, the objects are detected and mapped to the real-world location. Removing distortion from the image using camera calibration improves the accuracy in most of the cases. The deep learning framework Darknet is used for detection, and necessary modifications are made to integrate perspective transformation, camera calibration, un-distortion, etc. Experiments are performed with two types of cameras, one with barrel and the other with pincushion distortions. The results show that the difference between calculated distances and measured on real space with measurement tapes are very small; approximately 1 cm on an average. Furthermore, automatic corner detection allows the system to be used with any type of camera that has a fixed pose or in motion; using more points significantly enhances the accuracy of real-world mapping even without camera calibration. Perspective transformation also increases the object detection efficiency by making unified sizes of all objects.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.6
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• pp.382-390
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• 2021

The present study suggests the application of a depth camera for wave height field measurement, focusing on the calibration procedure and test setup. Azure Kinect system is used to measure the water surface elevation, with a field of view of 800 mm × 800 mm and repetition rate of 30 Hz. In the optimal optical setup, the spatial resolution of the field of view is 288 × 320 pixels. To detect the water surface by the depth camera, tracer particles that float on the water and reflects infrared is added. The calibration consists of wave height scaling and correction of the barrel distortion. A polynomial regression model of image correction is established using machine learning. The measurement results by the depth camera are compared with capacitance type wave height gauge measurement, to show good agreement.