• Title/Summary/Keyword: Intelligent image processing

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A Survey on User Interface Considering Social Acceptability based on Smart Glasses (스마트 글라스 기반의 사회적 수용성을 고려한 사용자 인터페이스 기존 연구 분석)

  • Lee, Minho;Heo, Hwan;Kim, Jaewoo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.10a
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    • pp.1160-1161
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    • 2019
  • Augmented Reality(AR) 기반의 스마트 글라스가 제공하는 일반적인 사용자 인터페이스는 카페 혹은 도서관 등과 같은 공공장소에서 사용이 꺼려지는 경향이 있다. 콘텐츠 조작 시 주변 사람들에게 관심을 받거나 프라이버시를 지키기 어렵기 때문이다. 이런 문제는 사회적으로 수용 가능한 범위 내에서의 사용자 인터페이스를 수행함으로써 해결할 수 있다. 본 논문에서는 스마트 글라스에서 사회적 수용성을 고려한 사용자 인터페이스의 기존 연구들을 분석하고자 한다.

Performance Evaluation of Lossy Compression to Occupancy Map in V-PCC (V-PCC의 점유 맵 손실 압축 성능 평가)

  • Park, Jong-Geun;Kim, Yura;Kim, Hyun-Ho;Kim, Yong-Hwan
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.06a
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    • pp.257-260
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    • 2022
  • 국제표준 3차원 포인트 클라우드 압축 기술인 MPEG(Moving Picture Experts Group)-I(Immersive) V-PCC(Video-based Point Cloud Compression)에는 점유 맵(Occupancy Map) 손실/무손실 압축 기술이 포함되어 있다. V-PCC는 기존에 보급되어 있는 2차원 비디오 코덱(H.264/AVC, HEVC, AV1 등)을 그대로 활용할 수 있는 장점이 있는데, 대부분의 소비자 영상 기기에 포함되어 있는 2차원 비디오 복호화기 HW는 무손실을 지원하지 않는다. 따라서 V-PCC 복호화기의 폭넓은 상용화를 위해서는 부호화기에서 점유 맵의 손실 압축이 필수적이다. 본 논문은 V-PCC 부호화기의 점유 맵을 최소한의 압축 효율 저하로 손실 압축하기 위해 다양한 파라미터 실험을 통한 최적의 파라미터 값을 제시한다.

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Tongue Image Segmentation via Thresholding and Gray Projection

  • Liu, Weixia;Hu, Jinmei;Li, Zuoyong;Zhang, Zuchang;Ma, Zhongli;Zhang, Daoqiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.945-961
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    • 2019
  • Tongue diagnosis is one of the most important diagnostic methods in Traditional Chinese Medicine (TCM). Tongue image segmentation aims to extract the image object (i.e., tongue body), which plays a key role in the process of manufacturing an automated tongue diagnosis system. It is still challenging, because there exists the personal diversity in tongue appearances such as size, shape, and color. This paper proposes an innovative segmentation method that uses image thresholding, gray projection and active contour model (ACM). Specifically, an initial object region is first extracted by performing image thresholding in HSI (i.e., Hue Saturation Intensity) color space, and subsequent morphological operations. Then, a gray projection technique is used to determine the upper bound of the tongue body root for refining the initial object region. Finally, the contour of the refined object region is smoothed by ACM. Experimental results on a dataset composed of 100 color tongue images showed that the proposed method obtained more accurate segmentation results than other available state-of-the-art methods.

Minimum Statistics-Based Noise Power Estimation for Parametric Image Restoration

  • Yoo, Yoonjong;Shin, Jeongho;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.2
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    • pp.41-51
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    • 2014
  • This paper describes a method to estimate the noise power using the minimum statistics approach, which was originally proposed for audio processing. The proposed minimum statistics-based method separates a noisy image into multiple frequency bands using the three-level discrete wavelet transform. By assuming that the output of the high-pass filter contains both signal detail and noise, the proposed algorithm extracts the region of pure noise from the high frequency band using an appropriate threshold. The region of pure noise, which is free from the signal detail part and the DC component, is well suited for minimum statistics condition, where the noise power can be extracted easily. The proposed algorithm reduces the computational load significantly through the use of a simple processing architecture without iteration with an estimation accuracy greater than 90% for strong noise at 0 to 40dB SNR of the input image. Furthermore, the well restored image can be obtained using the estimated noise power information in parametric image restoration algorithms, such as the classical parametric Wiener or ForWaRD image restoration filters. The experimental results show that the proposed algorithm can estimate the noise power accurately, and is particularly suitable for fast, low-cost image restoration or enhancement applications.

The Vaguelette-Curvelet Decomposition for Image Deblurring

  • Cho, Changhun;Katsaggelos, Aggelos K.;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • v.2 no.3
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    • pp.140-147
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    • 2013
  • We present a vaguelette-curvelet decomposition based image deblurring algorithm. We first perform denoising based on the hard-thresholding rule by estimating unknown curvelet coefficients. The proposed algorithm then calculates vaguelette functions by deconvolving the curvelet bases by the point spread function. Vaguelette transform is finally performed to make a clearly restored image. Since the proposed algorithm uses the curvelet transform to sensitively express the edges in all directions, it is possible to restore images with more naturally preserved edges in all directions.

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A Current Dynamic Analysis Based Open-Circuit Fault Diagnosis Method in Voltage-Source Inverter Fed Induction Motors

  • Tian, Lisi;Wu, Feng;Shi, Yi;Zhao, Jin
    • Journal of Power Electronics
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    • v.17 no.3
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    • pp.725-732
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    • 2017
  • This paper proposed a real-time, low-cost, fast transistor open-circuit fault diagnosis method for voltage-source inverter fed induction motors. A transistor open-circuit changes the symmetry of the inverter topology, leading to different similarities among three phase load currents. In this paper, dynamic time warping is proposed to describe the similarities among load currents. The proposed diagnosis is independent of the system model and needs no extra sensors or electrical circuits. Both simulation and experimental results show the high efficiency of the proposed fault diagnosis method.

IMAGE PROCESSING TECHNIQUES FOR LANE-RELATED INFORMATION EXTRACTION AND MULTI-VEHICLE DETECTION IN INTELLIGENT HIGHWAY VEHICLES

  • Wu, Y.J.;Lian, F.L.;Huang, C.P.;Chang, T.H.
    • International Journal of Automotive Technology
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    • v.8 no.4
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    • pp.513-520
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    • 2007
  • In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

Adaptive White Point Extraction based on Dark Channel Prior for Automatic White Balance

  • Jo, Jieun;Im, Jaehyun;Jang, Jinbeum;Yoo, Yoonjong;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.6
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    • pp.383-389
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    • 2016
  • This paper presents a novel automatic white balance (AWB) algorithm for consumer imaging devices. While existing AWB methods require reference white patches to correct color, the proposed method performs the AWB function using only an input image in two steps: i) white point detection, and ii) color constancy gain computation. Based on the dark channel prior assumption, a white point or region can be accurately extracted, because the intensity of a sufficiently bright achromatic region is higher than that of other regions in all color channels. In order to finally correct the color, the proposed method computes color constancy gain values based on the Y component in the XYZ color space. Experimental results show that the proposed method gives better color-corrected images than recent existing methods. Moreover, the proposed method is suitable for real-time implementation, since it does not need a frame memory for iterative optimization. As a result, it can be applied to various consumer imaging devices, including mobile phone cameras, compact digital cameras, and computational cameras with coded color.

Real-Time Continuous-Scale Image Interpolation with Directional Smoothing

  • Yoo, Yoonjong;Shin, Jeongho;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.3
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    • pp.128-134
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    • 2014
  • A real-time, continuous-scale image interpolation method is proposed based on a bilinear interpolation with directionally adaptive low-pass filtering. The proposed algorithm was optimized for hardware implementation. The ordinary bi-linear interpolation method has blocking artifacts. The proposed algorithm solves this problem using directionally adaptive low-pass filtering. The algorithm can also solve the severe blurring problem by selectively choosing low-pass filter coefficients. Therefore, the proposed interpolation algorithm can realize a high-quality image scaler for a range of imaging systems, such as digital cameras, CCTV and digital flat panel displays.

Emergency Detection Method using Motion History Image for a Video-based Intelligent Security System

  • Lee, Jun;Lee, Se-Jong;Park, Jeong-Sik;Seo, Yong-Ho
    • International journal of advanced smart convergence
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    • v.1 no.2
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    • pp.39-42
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    • 2012
  • This paper proposed a method that detects emergency situations in a video stream using MHI (Motion History Image) and template matching for a video-based intelligent security system. The proposed method creates a MHI of each human object through image processing technique such as background removing based on GMM (Gaussian Mixture Model), labeling and accumulating the foreground images, then the obtained MHI is compared with the existing MHI templates for detecting an emergency situation. To evaluate the proposed emergency detection method, a set of experiments on the dataset of video clips captured from a security camera has been conducted. And we successfully detected emergency situations using the proposed method. In addition, the implemented system also provides MMS (Multimedia Message Service) so that a security manager can deal with the emergency situation appropriately.