• Title/Summary/Keyword: camera image

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3D Conversion of 2D H.264 Video (2D H.264 동영상의 3D 입체 변환)

  • Hong, Ho-Ki;Baek, Yun-Ki;Lee, Seung-Hyun;Kim, Dong-Wook;Yoo, Ji-Sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.12C
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    • pp.1208-1215
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    • 2006
  • In this paper, we propose an algorithm that creates three-dimensional (3D) stereoscopic video from two-dimensional (2D) video encoded by H.264 instead of using the conventional stereo-camera process. Motion information of each frame can be obtained by the given motion vectors in most of videos encoded by MPEG standards. Especially, we have accurate motion vectors for H.264 streams because of the availability of a variety of block sizes. 2D/3D video conversion algorithm proposed in this paper can create the left and right images that correspond to the original image by using cut detection method, delay factors, motion types, and image types. We usually have consistent motion type na direction in a given cut because each frame in the same cut has high correlation. We show the improved performance of the proposed algorithm through experimental results.

Mobile Robot Control using Hand Shape Recognition (손 모양 인식을 이용한 모바일 로봇제어)

  • Kim, Young-Rae;Kim, Eun-Yi;Chang, Jae-Sik;Park, Se-Hyun
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.4
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    • pp.34-40
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    • 2008
  • This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

DIAGNOSIS OF EARLY CARIES WITH DYE-ENHANCED LASER FLUORESCENCE (레이저 형광과 광활성제를 이용한 초기 우식증의 진단)

  • Lee, Sang-Ho;Han, Kuk-Jae;Lee, Chang-Seop
    • Journal of the korean academy of Pediatric Dentistry
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    • v.30 no.1
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    • pp.1-9
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    • 2003
  • To evaluate the quantitative nature of laser fluorescence(LF) and dye-enhanced laser fluorescence(DELF) on early enamel caries, artificial caries were induced on the bovine enamels and argon laser was irradiated on the surfaces of lesions. Fluorescence radiance from enamel specimen was recorded with CCD camera which was connected to PC image analyzing system. The difference of fluorescence of radiance(DFR) between the carious and the sound enamel in each sample of the LF and the DELF groups were measured by image analyzing program. The DFR of lesion surfaces measured with laser fluorescence and lesion depths were evaluated and the results are as follows: The caries lesions were discriminated from sound enamels by the darkness with LF and by the brightness with DELF. The DELF was more sensitive than the LF at the earlier stage of demineralization.

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Emotion Classification Method Using Various Ocular Features (다양한 눈의 특징 분석을 통한 감성 분류 방법)

  • Kim, Yoonkyoung;Won, Myoung Ju;Lee, Eui Chul
    • The Journal of the Korea Contents Association
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    • v.14 no.10
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    • pp.463-471
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    • 2014
  • In this paper, emotion classification was performed by using four ocular features extracted from near-infrared camera image. According to comparing with previous work, the proposed method used more ocular features and each feature was validated as significant one in terms of emotion classification. To minimize side effects on ocular features caused by using visual stimuli, auditory stimuli for causing two opposite emotion pairs such as "positive-negative" and "arousal-relaxation" were used. As four features for emotion classification, pupil size, pupil accommodation rate, blink frequency, and eye cloased duration were adopted which could be automatically extracted by using lab-made image processing software. At result, pupil accommodation rate and blink frequency were statistically significant features for classification arousal-relaxation. Also, eye closed duration was the most significant feature for classification positive-negative.

Study of the Internal Flow and Evaporation Characteristic Inside a Water Droplet on a Vertical Vibrating Hydrophobic Surface (수직 진동을 이용한 가열된 고체표면 위 증발하는 액적의 내부유동 제어연구)

  • Park, Chang-Seok;Lim, Hee-Chang
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.41 no.1
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    • pp.37-46
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    • 2017
  • Thermal Marangoni flow has been observed inside droplets on heated surfaces, finally resulting in a coffee stain effect. This study aims to visualize and control the thermal Marangoni flow by employing periodic vertical vibration. The variations in the contact angle and internal volume of the droplet as it evaporates is observed by using a combination of continuous light and a still camera. With regard to the internal velocity, the particle image velocimetry system is applied to visualize the internal thermal Marangoni flow. In order to estimate the internal temperature gradient and surface tension on the surface of a droplet, the theoretical model based on the conduction and convection theory of heat transfer is applied. Thus, the internal velocity increases with an increase in plate temperature. The flow directions of the Marangoni and gravitational flows are opposite, and hence, it may be possible to control the coffee stain effect.

Thermal Imaging Fire Detection Algorithm with Minimal False Detection

  • Jeong, Soo-Young;Kim, Won-Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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    • pp.2156-2170
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    • 2020
  • This paper presents a fire detection algorithm with a minimal false detection rate, intended for a thermal imaging surveillance environment, whose properties vary depending on temporal conditions of day or night and environmental changes. This algorithm was designed to minimize the false detection alarm rate while ensuring a high detection rate, as required in fire detection applications. It was necessary to reduce false fire detections due to non-flame elements occurring when existing fixed threshold-based fire detection methods were applied. To this end, adaptive flame thresholds that varied depending on the characteristics of input images, as well as the center of gravity of the heat-source and hot-source regions, were analyzed in an attempt to minimize such non-flame elements in the phase of selecting flame candidate blocks. Also, to remove any false detection elements caused by camera shaking, one of the most frequently raised issues at outdoor sites, preliminary decision thresholds were adaptively set to the motion pixel ratio of input images to maximize the accuracy of the preliminary decision. Finally, in addition to the preliminary decision results, the texture correlation and intensity of the flame candidate blocks were averaged for a specific period of time and tested for their conformity with the fire decision conditions before making the final decision. To verify the fire detection performance of the proposed algorithm, a total of ten test videos were subjected to computer simulation. As a result, the fire detection accuracy of the proposed algorithm was determined to be 94.24%, with minimum false detection, demonstrating its improved performance and practicality compared to previous fixed threshold-based algorithms.

Hand gesture based a pet robot control (손 제스처 기반의 애완용 로봇 제어)

  • Park, Se-Hyun;Kim, Tae-Ui;Kwon, Kyung-Su
    • Journal of Korea Society of Industrial Information Systems
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    • v.13 no.4
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    • pp.145-154
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    • 2008
  • In this paper, we propose the pet robot control system using hand gesture recognition in image sequences acquired from a camera affixed to the pet robot. The proposed system consists of 4 steps; hand detection, feature extraction, gesture recognition and robot control. The hand region is first detected from the input images using the skin color model in HSI color space and connected component analysis. Next, the hand shape and motion features from the image sequences are extracted. Then we consider the hand shape for classification of meaning gestures. Thereafter the hand gesture is recognized by using HMMs (hidden markov models) which have the input as the quantized symbol sequence by the hand motion. Finally the pet robot is controlled by a order corresponding to the recognized hand gesture. We defined four commands of sit down, stand up, lie flat and shake hands for control of pet robot. And we show that user is able to control of pet robot through proposed system in the experiment.

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Establishment of Correspondent points and Sampling Period Needed to Estimate Object Motion Parameters (운동물체의 파라미터 추정에 필요한 대응점과 샘플링주기의 설정)

  • Jung, Nam-Chae;Moon, Yong-Sun;Park, Jong-An
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.5
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    • pp.26-35
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    • 1997
  • This paper deals with establishing correspondent points of feature pints and sampling period when we estimate object motion parameters from image information of freely moving objects in space of gravity-free state. Replacing the inertial coordinate system with the camera coordinate system which is equipped within a space robot, it is investigated to be able to analyze a problem of correspond points from image information, and to obtain sequence of angular velocity $\omega$ which determine a motion of object by means of computer simulation. And if a sampling period ${\Delta}t$ is shortened, the relative errors of angular velocity are increased because the relative errors against moving distance of feature points are increased by quantization. In reverse, if a sampling period ${\Delta}t$ is lengthened too much, the relative error are likewise increased because a sampling period is long for angular velocity to be approximated, and we confirmed the precision that grows according to ascending of resolution.

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Luminance Correction for Stereo Images using Histogram Interval Calibration (히스토그램 구간 교정을 이용한 스테레오 영상의 휘도 보정)

  • Kim, Seaho;Kim, Hiseok
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.12
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    • pp.159-167
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    • 2013
  • In stereo-view system, variations of target camera position or lighting conditions cause discrepancies on the luminance and chrominance components of stereo views. These discrepancies lead to inaccurate frame view prediction and low quality of 3 D video coding. In this paper, an efficient histogram interval calibration method is proposed for stereo-view coding, so as to compensate for the luminance component of target view. First the proposed method is analyzed by the histogram of the target image frame. Then, it divide two sections of histogram of that frame to correct the color discrepancies. Secondly, each section of the target frame is corrected the luminance component by identify the maximum matching region between the reference frame and the target frame. We have verified our proposed histogram matching method in comparison with the other color correction ones. Experimental results show that it can correct better luminance calibration results of PSNR(Peak Signal to Noise Ratio) and has less computation time.

An Efficient Pedestrian Recognition Method based on PCA Reconstruction and HOG Feature Descriptor (PCA 복원과 HOG 특징 기술자 기반의 효율적인 보행자 인식 방법)

  • Kim, Cheol-Mun;Baek, Yeul-Min;Kim, Whoi-Yul
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.10
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    • pp.162-170
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    • 2013
  • In recent years, the interests and needs of the Pedestrian Protection System (PPS), which is mounted on the vehicle for the purpose of traffic safety improvement is increasing. In this paper, we propose a pedestrian candidate window extraction and unit cell histogram based HOG descriptor calculation methods. At pedestrian detection candidate windows extraction stage, the bright ratio of pedestrian and its circumference region, vertical edge projection, edge factor, and PCA reconstruction image are used. Dalal's HOG requires pixel based histogram calculation by Gaussian weights and trilinear interpolation on overlapping blocks, But our method performs Gaussian down-weight and computes histogram on a per-cell basis, and then the histogram is combined with the adjacent cell, so our method can be calculated faster than Dalal's method. Our PCA reconstruction error based pedestrian detection candidate window extraction method efficiently classifies background based on the difference between pedestrian's head and shoulder area. The proposed method improves detection speed compared to the conventional HOG just using image without any prior information from camera calibration or depth map obtained from stereo cameras.