• Title/Summary/Keyword: motion image

Search Result 2,144, Processing Time 0.03 seconds

Adaptive Enhancement Method for Robot Sequence Motion Images

  • Yu Zhang;Guan Yang
    • Journal of Information Processing Systems
    • /
    • v.19 no.3
    • /
    • pp.370-376
    • /
    • 2023
  • Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.

Motion Segmentation for Layer Decomposition of Image Sequences (영상 시퀀스의 계층 분리를 위한 움직임 분할)

  • 장정진;오정수;홍현기;최종수
    • Proceedings of the IEEK Conference
    • /
    • 2000.11d
    • /
    • pp.29-32
    • /
    • 2000
  • This paper proposes a motion segmentation algorithm for layer decomposition of image sequences. The proposed algorithm segments an image into initial regions by using its color and texture and computes a motion model of each initial region. Each pixel assigns one of the motion represented by the models or a motion except them, which segments the image into the motion regions. The proposed algorithm is app]ied image sequences and the segmented motion is shown.

  • PDF

Stereoscopic Video Conversion Based on Image Motion Classification and Key-Motion Detection from a Two-Dimensional Image Sequence (영상 운동 분류와 키 운동 검출에 기반한 2차원 동영상의 입체 변환)

  • Lee, Kwan-Wook;Kim, Je-Dong;Kim, Man-Bae
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.34 no.10B
    • /
    • pp.1086-1092
    • /
    • 2009
  • Stereoscopic conversion has been an important and challenging issue for many 3-D video applications. Usually, there are two different stereoscopic conversion approaches, i.e., image motion-based conversion that uses motion information and object-based conversion that partitions an image into moving or static foreground object(s) and background and then converts the foreground in a stereoscopic object. As well, since the input sequence is MPEG-1/2 compressed video, motion data stored in compressed bitstream are often unreliable and thus the image motion-based conversion might fail. To solve this problem, we present the utilization of key-motion that has the better accuracy of estimated or extracted motion information. To deal with diverse motion types, a transform space produced from motion vectors and color differences is introduced. A key-motion is determined from the transform space and its associated stereoscopic image is generated. Experimental results validate effectiveness and robustness of the proposed method.

The Application of Dynamic Acquisition with Motion Correction for Static Image (동적 영상 획득 방식을 이용한 정적 영상의 움직임 보정)

  • Yoon, Seok-Hwan;Seung, Jong-Min;Kim, Kye-Hwan;Kim, Jae-Il;Lee, Hyung-Jin;Kim, Jin-Eui;Kim, Hyun-Joo
    • The Korean Journal of Nuclear Medicine Technology
    • /
    • v.14 no.1
    • /
    • pp.46-53
    • /
    • 2010
  • Purpose: The static image of nuclear medicine study should be acquired without a motion, however, it is difficult to acquire static image without movement for the serious patients, advanced aged patients. These movements cause decreases in reliability for quantitative and qualitative analysis, therefore re-examination was inevitable in the some cases. Consequently, in order to improve the problem of motion artifacts, the authors substituted the dynamic acquisition technique for the static acquisition, using motion correction. Materials and Methods: A capillary tube and IEC body phantom were used. First, the static image was acquired for 60 seconds while the dynamic images were acquired with a protocol, 2 sec/frame${\times}$30 frames, under the same parameter and the frames were summed up into one image afterwards. Also, minimal motion and excessive motion were applied during the another dynamic acquisition and the coordinate correction was applied towards X and Y axis on the frames where the motion artifact occurred. But the severe blurred images were deleted. Finally, the resolution and counts were compared between the static image and the summed dynamic images which before and after applying motion correction, and the signal of frequency was analysed after frequency spatial domain was transformed into 2D FFT. Supplementary examination, the blind test was performed by the nuclear medicine department staff. Results: First, the resolution in the static image and summed dynamic image without motion were 8.32 mm, 8.37 mm on X-axis and 8.30 mm, 8.42 mm on Y-axis, respectively. The counts were 484 kcounts, 485 kcounts each, so there was nearly no difference. Secondly, the resolution in the image with minimal motion applying motion correction was 8.66 mm on X-axis, 8.85 mm on Y-axis and had 469 kcounts while the image without motion correction was 21.81 mm, 24.02 mm and 469 kcounts in order. So, this shows the image with minimal motion applying motion correction has similar resolution with the static image. Lastly, the resolution in the images with excessive motion applying motion correction were 9.09 mm on X-axis, 8.83 mm on Y-axis and had 469 kcounts while the image without motion correction was 47.35 mm, 40.46 mm and 255 kcounts in order. Although there was difference in counts because of deletion of blurred frames, we could get similar resolution. And when the image was transformed into frequency, the high frequency was decreased by the movement. However, the frequency was improved again after motion correction. In the blind test, there was no difference between the image applying motion correction and the static image without motion. Conclusion: There was no significant difference between the static image and the summed dynamic image. This technique can be applied to patients who may have difficulty remaining still during the imaging process, so that the quality of image can be improved as well as the reliance for analysis of quantity. Moreover, the re-examination rate will be considerably decreased. However, there is a limit of motion correction, more time will be required to successfully image the patients applying motion correction. Also, the decrease of total counts due to deletion of the severe blurred images should be calculated and the proper number of frames should be acquired.

  • PDF

Joint Overlapped Block Motion Compensation Using Eight-Neighbor Block Motion Vectors for Frame Rate Up-Conversion

  • Li, Ran;Wu, Minghu;Gan, Zongliang;Cui, Ziguan;Zhu, Xiuchang
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.7 no.10
    • /
    • pp.2448-2463
    • /
    • 2013
  • The traditional block-based motion compensation methods in frame rate up-conversion (FRUC) only use a single uniquely motion vector field. However, there will always be some mistakes in the motion vector field whether the advanced motion estimation (ME) and motion vector analysis (MA) algorithms are performed or not. Once the motion vector field has many mistakes, the quality of the interpolated frame is severely affected. In order to solve the problem, this paper proposes a novel joint overlapped block motion compensation method (8J-OBMC) which adopts motion vectors of the interpolated block and its 8-neighbor blocks to jointly interpolate the target block. Since the smoothness of motion filed makes the motion vectors of 8-neighbor blocks around the interpolated block quite close to the true motion vector of the interpolated block, the proposed compensation algorithm has the better fault-tolerant capability than traditional ones. Besides, the annoying blocking artifacts can also be effectively suppressed by using overlapped blocks. Experimental results show that the proposed method is not only robust to motion vectors estimated wrongly, but also can to reduce blocking artifacts in comparison with existing popular compensation methods.

An Observation System of Hemisphere Space with Fish eye Image and Head Motion Detector

  • Sudo, Yoshie;Hashimoto, Hiroshi;Ishii, Chiharu
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 2003.10a
    • /
    • pp.663-668
    • /
    • 2003
  • This paper presents a new observation system which is useful to observe the scene of the remote controlled robot vision. This system is composed of a motionless camera and head motion detector with a motion sensor. The motionless camera has a fish eye lens and is for observing a hemisphere space. The head motion detector has a motion sensor is for defining an arbitrary subspace of the hemisphere space from fish eye lens. Thus processing the angular information from the motion sensor appropriately, the direction of face is estimated. However, since the fisheye image is distorted, it is unclear image. The partial domain of a fish eye image is selected by head motion, and this is converted to perspective image. However, since this conversion enlarges the original image spatially and is based on discrete data, crevice is generated in the converted image. To solve this problem, interpolation based on an intensity of the image is performed for the crevice in the converted image (space problem). This paper provides the experimental results of the proposed observation system with the head motion detector and perspective image conversion using the proposed conversion and interpolation methods, and the adequacy and improving point of the proposed techniques are discussed.

  • PDF

A Guideline for Motion-Image-Quality Improvement of LCD-TVs

  • Kurita, Taiichiro
    • 한국정보디스플레이학회:학술대회논문집
    • /
    • 2009.10a
    • /
    • pp.1164-1167
    • /
    • 2009
  • Motion-image-quality of LCD-TVs is discussed by dynamic spatial frequency response. Smaller temporal aperture or higher frame rate can improve dynamic response, but an increase of motion velocity easily cancels the improvement. A guideline for deciding the desirable temporal aperture and frame rate of LCD-TVs is described, under the condition that camera and display have the same parameters. Two candidates of the desirable parameter sets will be (240 or 300 Hz, 50 to 100% aperture) and (120Hz, 25 to 50% aperture), from the viewpoint of "limit of acceptance" on motion-imagequality-deterioration for critical picture materials.

  • PDF

A General Representation of Motion Silhouette Image: Generic Motion Silhouette Image(GMSI) (움직임 실루엣 영상의 일반적인 표현 방식에 대한 연구)

  • Hong, Sung-Jun;Lee, Hee-Sung;Kim, Eun-Tai
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.13 no.8
    • /
    • pp.749-753
    • /
    • 2007
  • In this paper, a generalized version of the Motion Silhouette Image(MSI) called the Generic Motion Silhouette Image (GMSI) is proposed for gait recognition. The GMSI is a gray-level image and involves the spatiotemporal information of individual motion. The GMSI not only generalizes the MSI but also reflects a flexible feature of a gait sequence. Along with the GMSI, we use the Principal Component Analysis(PCA) to reduce the dimensionality of the GMSI and the Nearest Neighbor(NN) for classification. We apply the proposed feature to NLPR database and compare it with the conventional MSI. Experimental results show the effectiveness of the GMSI.

Motion Detection using Adaptive Background Image and Pixel Space (적응적 배경영상과 픽셀 간격을 이용한 움직임 검출)

  • 지정규;이창수;오해석
    • Journal of Information Technology Applications and Management
    • /
    • v.10 no.3
    • /
    • pp.45-54
    • /
    • 2003
  • Security system with web camera remarkably has been developed at an Internet era. Using transmitted images from remote camera, the system can recognize current situation and take a proper action through web. Existing motion detection methods use simply difference image, background image techniques or block matching algorithm which establish initial block by set search area and find similar block. But these methods are difficult to detect exact motion because of useless noise. In this paper, the proposed method is updating changed background image as much as $N{\times}M$pixel mask as time goes on after get a difference between imput image and first background image. And checking image pixel can efficiently detect motion by computing fixed distance pixel instead of operate all pixel.

  • PDF

3D FACE RECONSTRUCTION FROM ROTATIONAL MOTION

  • Sugaya, Yoshiko;Ando, Shingo;Suzuki, Akira;Koike, Hideki
    • Proceedings of the Korean Society of Broadcast Engineers Conference
    • /
    • 2009.01a
    • /
    • pp.714-718
    • /
    • 2009
  • 3D reconstruction of a human face from an image sequence remains an important problem in computer vision. We propose a method, based on a factorization algorithm, that reconstructs a 3D face model from short image sequences exhibiting rotational motion. Factorization algorithms can recover structure and motion simultaneously from one image sequence, but they usually require that all feature points be well tracked. Under rotational motion, however, feature tracking often fails due to occlusion and frame out of features. Additionally, the paucity of images may make feature tracking more difficult or decrease reconstruction accuracy. The proposed 3D reconstruction approach can handle short image sequences exhibiting rotational motion wherein feature points are likely to be missing. We implement the proposal as a reconstruction method; it employs image sequence division and a feature tracking method that uses Active Appearance Models to avoid the failure of feature tracking. Experiments conducted on an image sequence of a human face demonstrate the effectiveness of the proposed method.

  • PDF