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IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

作者： Yeongbin Kim Hasil Park Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea

This paper presents a robust tracking algorithm using convolutional features. The proposed tracking algorithm consists of three steps: i) training correlation filters using features extracted by a convolutional neural network, ii) localizing the target position in the next frame by multiplying weight and correlation response of each layer, and iii) re-training correlation filters every 10-frame using the proposed position error score. Experimental results show that the proposed algorithm outperforms an existing deep learning-based tracker.

关键词： Correlation Feature extraction Target tracking Pattern recognition Object tracking image color analysis Silicon

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WAVELENGTH-ADAPTIVE image FORMATION MODEL AND GEOMETRIC CLASSIFICATION FOR DEFOGGING UNMANNED AERIAL VEHICLE imageS

WAVELENGTH-ADAPTIVE IMAGE FORMATION MODEL AND GEOMETRIC CLAS...

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Inhye Yoon Monson H. Hayes Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea

ISBN: (纸本)9781479903573

In this paper, we present an image enhancement algorithm based on the wavelength-adaptive image formation model and geometric classification for defogging UAV images. We first generate a labeled image using geometric class-based segmentation. We then generate a modified transmission map based on the wavelength-adaptive image formation model with scattering coefficients in the labeled image. We also estimate the atmospheric light from the modified transmission map instead of simply choosing the brightest pixel. The proposed method can significantly enhance the visibility of foggy UAV images compared with existing monochrome model-based defogging method. The proposed algorithm can enhance the visibility by removing atmospheric degradation factor in airborne images acquired by aerial platforms such as satellite, airplane, and UAV under critical weather conditions such as haze, fog, and smoke.

关键词： image enhancement image defogging unmanned aerial vehicle image enhancement images drone honey bees Unmanned Aerial Vehicle vehicle image enhancement algorithm image formation aerial platforms UNMANNED visibility ANTENNA Scattering coefficient BRIGHT

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Deep learning-based number detection and recognition for gas meter reading

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IEIE Transactions on Smart processing and Computing 2019年第5期8卷 367-372页

作者： Son, Changeui Park, Seokmok Lee, JaeMin Paik, Joonki Department of Image Engineering Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul06974 Korea Republic of

The meter reading-system field has been researched from conventional methods centered on image processing technology to techniques based on learning methods such as machine learning or deep learning. The biggest problem for meter reading systems based on computer vision is difficulty in recognizing the various kinds of meters. In fact, there are more than five major manufacturers for the meters installed in Korea. There are different meter reading areas, ID regions, and number formats by version. Because of these problems, most of the meter reading is still done hands-on. In this paper, we present an automatic meter-reading system that can work simply and efficiently, compared to existing meter reading systems that need a skilled worker. Our meter reading system consists of three parts: i) detection of meter-reading and ID regions using You Only Look Once (YOLO), ii) digit segmentation for recognition, and iii) convolutional neural network (CNN)-based digit recognition. It is possible to robustly detect and recognize various meter types by using the method presented here. Therefore, it can provide an environment where gas meter checkers can work efficiently without inconvenient procedures. Copyrights © 2019 The Institute of Electronics and Information Engineers

关键词： Computer vision

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Wavelet-based enhancement of color image using combined local variance and entropy analysis

Wavelet-based enhancement of color image using combined loca...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Sinyoung Jun Eunsung Lee Sangjin Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)9781424443147

This paper presents a novel wavelet-based image enhancement approach to reduce noise in a single-sensor color camera. Most traditional noise reduction methods tend to over-suppress high-frequency details. For overcoming this problem we first decompose the input image into flat and edge regions, and adaptively remove noise by multiplying alpha map and wavelet transform coefficients of LH, HL, and HH bands. After removing noise in the flat region, we further remove noise in edge regions by adaptive shrink of wavelet coefficients based on the entropy. Experimental result show the proposed algorithm is proved to be able to reduce noise without losing sharp details and is suitable for commercial low-cost such as digital cameras, CCTV, and surveillance systems.

关键词： Wavelet analysis Entropy Analysis of variance image analysis image color analysis Noise reduction Colored noise image enhancement Cameras Wavelet transforms

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image restoration using alpha map-based fusion for multiple color aperture computational camera

Image restoration using alpha map-based fusion for multiple ...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Eunsung Lee Vivek Maik Sinyoung Jun Sangjin Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)9781424443147;9781424443161

We present a novel image restoration approach by fusing multiple images acquired by a multiple color aperture computational camera for overcoming the limit of conventional image restoration algorithms, such as high computational load and post-processing artifacts. The proposed restoration framework utilizes color matching, alignment, and fusion of multiple images acquired by using multiple color apertures. The alpha map-based image fusion step successfully restores high-frequency components of meaningful edge regions. The proposed scheme can achieve automatic focusing and varying depth of filed at low cost for low-end consumer cameras.

关键词： image restoration Apertures Focusing Signal processing algorithms Color image fusion Smart cameras Costs Digital images Educational technology

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Vaguelette-wavelet decomposition for real-time image restoration using directional wavelet bases

Vaguelette-wavelet decomposition for real-time image restora...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Wonseok Kang Eunsung Lee Sangjin Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

Conventional image restoration filters, such as Wiener filter, often exhibit either noise amplification or over-smoothing problem. On the other hand, advanced image restoration techniques, such as iterative regularization or combined Fourier and wavelet domain thresholding techniques, is not suitable for real-time application because of high computational overhead. For overcoming these problems, we adopt vaguelette-wavelet decomposition (VWD) approach to realtime, space-frequency adaptive image restoration based on the estimated point spread-function (PSF) and directional wavelet bases.

关键词： image restoration Wavelet transforms Low pass filters Filtering algorithms Real time systems Noise

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Single image-based depth estimation using dual off-axis color filtered aperture camera

Single image-based depth estimation using dual off-axis colo...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Seungwon Lee Nahyun Kim Kyungwon Jung Monson H. Hayes Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)9781479903573

In this paper, we present a dual off-axis color filtered aperture (DCA)-based computational imaging system for depth estimation in a single-camera framework. The DCA has one primary (red) color and its complementary (cyan) color filtered apertures located off the optical axis to generate misalignment between color channels depending on the distance of a region-of-interest from the camera. Disparity of color shifting values (CSVs) between color channels in the image acquired by the DCA-based imaging system is estimated using L 1 -norm minimization of energy functional considering both brightness and gradient constancies and only translation of x-axis. The two data terms both red to green (R-G) and red to blue (R-B) are combined in a single data term. The proposed imaging system can be implemented by simply inserting an appropriately resized DCA into any general optical system. Experimental results show that the proposed DCA can estimate the distance of the scene from the camera in the single-camera framework.

关键词： image color analysis Cameras Apertures Estimation Optical imaging Channel estimation

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Plane identification and segmentation from uncalibrated stereo based on evolutionary approach

Plane identification and segmentation from uncalibrated ster...

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IEEE International Symposium on intelligent Signal processing and Communication systems (ISPACS)

作者： Junghoon Jung Taekyung Kim Ohyun Kwon Joonki Paik Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)0780386396

Planes are widely used in various vision tasks due to their abundance especially in man-made environments. Assuming an uncalibrated stereo image acquisition system, we propose a new plane identification and segmentation algorithm using an evolutionary approach. The proposed algorithm enables faster and more robust estimation of the plane since it progressively searches the best solution in a guided direction. Experimental results show that the proposed algorithm has higher performance than the existing method.

关键词： image segmentation Iterative algorithms Evolutionary computation Robustness Transmission line matrix methods image processing intelligent systems Laboratories Multimedia systems Electronic mail

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Wavelet transform-based hierarchical active shape model for object tracking

Wavelet transform-based hierarchical active shape model for ...

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IEEE International Symposium on intelligent Signal processing and Communication systems (ISPACS)

作者： Hyunjong Ki Jeonho Shin Joonki Paik Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)0780386396

This paper proposes a hierarchical approach to the active shape model (ASM) using a wavelet transform. Local structure model fitting in the ASM plays an important role in model-based pose and shape analysis. The proposed algorithm can robustly find good solutions in complex images by using wavelet decomposition. We also describe how to apply Kalman filtering for ASM-based, real-time video tracking. The proposed algorithm has been tested for various sequences containing human motion to demonstrate the improved performance of the proposed object tracking.

关键词： Active shape model Humans Robustness Kalman filters Filtering image analysis image processing intelligent systems Laboratories Multimedia systems

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Enhanced active shape model using evolutionary computation and its extension to RGB color space

Enhanced active shape model using evolutionary computation a...

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IEEE International Symposium on intelligent Signal processing and Communication systems (ISPACS)

作者： V. Maik Hyunjong Ki Sangjin Kim Jeongho Shin Seongwon Lee L. Paik Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

This paper deals with an application of evolutionary computation to active shape model (ASM) for locating and analyzing objects an image. The ASM algorithm has proved to be a successful method for segmentation of objects in gray-scale images. However, a number of modifications and extensions to the basic ASM algorithm have been proposed to cope up with various limitations. The proposed method in this paper relies on two such extensions: (i) evolutionary algorithm for better local structure model; and (ii) incorporation of color information for solving the outlier problem in model fitting.

关键词： Active shape model Evolutionary computation Humans Biological system modeling Application software Deformable models Robustness Colored noise Noise shaping image processing

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