Image-Based Method

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Kazi Mostafa - One of the best experts on this subject based on the ideXlab platform.

  • Image-Based Method for Determining Better Walking Strategies for Hexapods
    International Journal of Advanced Robotic Systems, 2015
    Co-Authors: Kazi Mostafa, John Y. Chiang
    Abstract:

    An intelligent walking strategy is vital for multi-legged robots possessing no a priori information of an environment when traversing across discontinuous terrain. Six-legged robots outperform other multi-legged robots in static and dynamic stability. However, hexapods require careful planning to traverse across discontinuous terrain. A hexapod walking strategy can be accomplished using a vision-based navigation system to identify the surrounding environment. This paper presents an Image-Based technique to achieve better walking strategies for a hexapod walking on a special terrain containing irregular, restricted regions. The properties of the restricted regions were acquired beforehand by using reliable surveillance means. Moreover, simplified forward gaits, better rotational gaits, and adaptive gait selection strategies for walking on discontinuous terrain were proposed. The hexapod can effectively switch the gait sequences and types according to the environment involved. The boundary of standing zones...

  • An image based Method of finding better walking strategies for hexapod on discontinuous terrains
    2012 IEEE ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2012
    Co-Authors: Kazi Mostafa
    Abstract:

    The adaptive gait planning is an important aspect for walking robot traversing on rough terrain. Hexapod robot is robust among all legged robots walking over rough terrain. For rough terrain, many studies have been performed on robot vision system to recognize the surrounding terrain. But those studies are based on simple rule of forbidden walking regions of the robot. This paper presented a special image based Method to recognize the surrounding terrain. Moreover, a number of parameters used to establish, modify, and analyze the terrain. A hexapod robot walking gait model also designed to test the effectiveness of proposed Method. Simulation results show that the Method can handle large databases with image processing technique to find out the optimum strategy of walking on rough terrain.

Filippo Piccinini - One of the best experts on this subject based on the ideXlab platform.

  • Vignetting and photo-bleaching correction in automated fluorescence microscopy from an array of overlapping images
    2013 IEEE 10th International Symposium on Biomedical Imaging, 2013
    Co-Authors: Filippo Piccinini, Alessandro Bevilacqua, Kevin Smith, Peter Horvath
    Abstract:

    We propose a novel acquisition scheme and non-parametric multi-image based Method for correcting illumination in fluorescence images. Our approach measures changes in intensity of the subject by moving the microscope stage at regularly spaced intervals, and exploits this information to learn the correction function. The acquisition process and learning are performed prior to imaging, and take only a few minutes. Afterwards, images can be corrected for vignetting and photobleaching effects on the fly. Our approach can be implemented in any microscope with a motorized stage, and does not require a reference calibration slide. Experiments demonstrate that our Method outperforms standard approaches to illumination correction.

  • Multi‐image based Method to correct vignetting effect in light microscopy images
    Journal of Microscopy, 2012
    Co-Authors: Filippo Piccinini, Enrico Lucarelli, Alessandro Gherardi, Alessandro Bevilacqua
    Abstract:

    Summary Vignetting is the radial attenuation effect of the image's brightness intensity from the center of the optical axis to the edges. To perform quantitative image analyses it is mandatory to take into account this effect, intrinsic of the acquisition system. Many image processing steps, such as segmentation and object tracking, are strongly affected by vignetting and the effect becomes particularly evident in mosaicing. The most common approach to compensate the attenuation of the image's brightness intensity is to estimate the vignetting function from a homogeneous reference object, typically an empty field, and to use it to normalize the images acquired under the same microscope set-up conditions. However, several reasons lead to the use of Image-Based Methods to estimate the vignetting function from the images themselves. In this work, we propose an effective multi-image based Method suitable for real-time applications. It is designed to correct vignetting in wide field light microscopy images. The vignetting function is computed stemming from a background built incrementally from the proposed background segmentation algorithm, validated on several manually segmented images. The extensive experiments carried out using cell cultures, histological samples and synthetic images prove that our Method almost always yields the best results and in worst cases are comparable to those achieved by using homogeneous reference objects.

Jim Ji - One of the best experts on this subject based on the ideXlab platform.

  • ICIoT - An Image-Based Method for Soiling Quantification
    2020 IEEE International Conference on Informatics IoT and Enabling Technologies (ICIoT), 2020
    Co-Authors: Mingda Yang, Jim Ji
    Abstract:

    Soiling due to dust accumulation reduces solar energy conversion efficiency in solar photovoltaic (PV) power generation. In this study, a preliminary investigation of using image analysis to quantify soiling on a surrogate surface is carried out. The effect of several camera settings is investigated in a lab environment where ground-truth dust loading can be measured gravimetrically. Specifically, a custom black-and-white pattern with various levels of dust loading is imaged by visible light photography at various shutter speed, aperture, and focus conditions. We develop an image analysis Method to extract black and white regions from the photo, based on which a metric called black/white ratio (BWR) is calculated. Quantitative relations between BWR and the dust loading level, namely dust mass per unit area of the black-and-white pattern, are investigated under different conditions. The results from this study demonstrate the feasibility of using image attributes of a dust-covered solar module, or a surrogate surface, to quantify soiling loss and indicate the need for further research to understand the complex effects of various factors on this approach.

  • An Image-Based Method for Soiling Quantification
    2020 IEEE International Conference on Informatics IoT and Enabling Technologies (ICIoT), 2020
    Co-Authors: Mingda Yang, Jim Ji
    Abstract:

    Soiling due to dust accumulation reduces solar energy conversion efficiency in solar photovoltaic (PV) power generation. In this study, a preliminary investigation of using image analysis to quantify soiling on a surrogate surface is carried out. The effect of several camera settings is investigated in a lab environment where ground-truth dust loading can be measured gravimetrically. Specifically, a custom black-and-white pattern with various levels of dust loading is imaged by visible light photography at various shutter speed, aperture, and focus conditions. We develop an image analysis Method to extract black and white regions from the photo, based on which a metric called black/white ratio (BWR) is calculated. Quantitative relations between BWR and the dust loading level, namely dust mass per unit area of the black-and-white pattern, are investigated under different conditions. The results from this study demonstrate the feasibility of using image attributes of a dust-covered solar module, or a surrogate surface, to quantify soiling loss and indicate the need for further research to understand the complex effects of various factors on this approach.

Alessandro Bevilacqua - One of the best experts on this subject based on the ideXlab platform.

  • Vignetting and photo-bleaching correction in automated fluorescence microscopy from an array of overlapping images
    2013 IEEE 10th International Symposium on Biomedical Imaging, 2013
    Co-Authors: Filippo Piccinini, Alessandro Bevilacqua, Kevin Smith, Peter Horvath
    Abstract:

    We propose a novel acquisition scheme and non-parametric multi-image based Method for correcting illumination in fluorescence images. Our approach measures changes in intensity of the subject by moving the microscope stage at regularly spaced intervals, and exploits this information to learn the correction function. The acquisition process and learning are performed prior to imaging, and take only a few minutes. Afterwards, images can be corrected for vignetting and photobleaching effects on the fly. Our approach can be implemented in any microscope with a motorized stage, and does not require a reference calibration slide. Experiments demonstrate that our Method outperforms standard approaches to illumination correction.

  • Multi‐image based Method to correct vignetting effect in light microscopy images
    Journal of Microscopy, 2012
    Co-Authors: Filippo Piccinini, Enrico Lucarelli, Alessandro Gherardi, Alessandro Bevilacqua
    Abstract:

    Summary Vignetting is the radial attenuation effect of the image's brightness intensity from the center of the optical axis to the edges. To perform quantitative image analyses it is mandatory to take into account this effect, intrinsic of the acquisition system. Many image processing steps, such as segmentation and object tracking, are strongly affected by vignetting and the effect becomes particularly evident in mosaicing. The most common approach to compensate the attenuation of the image's brightness intensity is to estimate the vignetting function from a homogeneous reference object, typically an empty field, and to use it to normalize the images acquired under the same microscope set-up conditions. However, several reasons lead to the use of Image-Based Methods to estimate the vignetting function from the images themselves. In this work, we propose an effective multi-image based Method suitable for real-time applications. It is designed to correct vignetting in wide field light microscopy images. The vignetting function is computed stemming from a background built incrementally from the proposed background segmentation algorithm, validated on several manually segmented images. The extensive experiments carried out using cell cultures, histological samples and synthetic images prove that our Method almost always yields the best results and in worst cases are comparable to those achieved by using homogeneous reference objects.

Thomas P. Andriacchi - One of the best experts on this subject based on the ideXlab platform.

  • An automated Image-Based Method of 3D subject-specific body segment parameter estimation for kinetic analyses of rapid movements.
    Journal of Biomechanical Engineering-transactions of The Asme, 2009
    Co-Authors: Alison L. Sheets, Stefano Corazza, Thomas P. Andriacchi
    Abstract:

    Accurate subject-specific body segment parameters (BSPs) are necessary to perform kinetic analyses of human movements with large accelerations, or no external contact forces or moments. A new automated topographical Image-Based Method of estimating segment mass, center of mass (CM) position, and moments of inertia is presented. Body geometry and volume were measured using a laser scanner, then an automated pose and shape registration algorithm segmented the scanned body surface, and identified joint center (JC) positions. Assuming the constant segment densities of Dempster, thigh and shank masses, CM locations, and moments of inertia were estimated for four male subjects with body mass indexes (BMIs) of 19.7–38.2. The subject-specific BSP were compared with those determined using Dempster and Clauser regression equations. The influence of BSP and BMI differences on knee and hip net forces and moments during a running swing phase were quantified for the subjects with the smallest and largest BMIs. Subject-specific BSP for 15 body segments were quickly calculated using the Image-Based Method, and total subject masses were overestimated by 1.7–2.9%.When compared with the Dempster and Clauser Methods, Image-Based and regression estimated thigh BSP varied more than the shank parameters. Thigh masses and hip JC to thigh CM distances were consistently larger, and each transverse moment of inertia was smaller using the Image-Based Method. Because the shank had larger linear and angular accelerations than the thigh during the running swing phase, shank BSP differences had a larger effect on calculated intersegmental forces and moments at the knee joint than thigh BSP differences did at the hip. It was the net knee kinetic differences caused by the shank BSP differences that were the largest contributors to the hip variations. Finally, BSP differences produced larger kinetic differences for the subject with larger segment masses, suggesting that parameter accuracy is more important for studies focused on overweight populations. The new Image-Based BSP estimation Method described in this paper addressed the limitations of currently used geometric and regression Methods by using exact limb geometry to determine subject-specific parameters. BSP differences have the largest effect on kinetic analyses of motions with large limb accelerations, for joints farther along the kinematic chain from the known forces and moments, and for subjects with larger limb masses or BMIs.

  • An Automated Image-Based Method of 3D Subject Specific Body Segment Parameter Estimation
    ASME 2008 Summer Bioengineering Conference Parts A and B, 2008
    Co-Authors: Alison L. Sheets, Stefano Corazza, Thomas P. Andriacchi
    Abstract:

    Recent studies have suggested that limb kinetics during swing or float phase movements are important for ACL injury analysis and injury prevention [1]. Kinetic (moment and force) calculations during swing phase can be sensitive to the accuracy of subject-specific body segment parameters (BSP) including mass and inertial properties. While numerous Methods for estimating BSP have been implemented including regression equations [2,3], geometric body shape estimations, medical imaging and optimization approaches, they all have application specific limitations. Almost all of these BSP estimation approaches are limited by assumptions that: the mass center (CM) lies on the axis connecting the segment’s proximal and distal joint center, the body principle moments of inertia are aligned with the segment axes [4], and the right and left limbs are symmetric. These assumptions could introduce errors in 3D kinematic analysis. Non-invasive Methods of measuring the exact geometry and volume of body segments have the potential to reduce most sources of error.Copyright © 2008 by ASME