Image-based Measurement Systems Research Articles

Image-Based Measurement of Wave Interactions with Rubble Mound Breakwaters

Over the past decade, the use of imaging devices to perform quantitative measurements has seen wide-scale adoption and has become integral to the emerging fields of research, such as computer vision and artificial intelligence. Recent studies, published across a wide variety of fields, have demonstrated a vast number of ways through which image-based measurement systems can be used in their respective fields. A growing number of studies have demonstrated applications in coastal and ocean research. Edge detection methods have been used to measure water surface and bedform elevation from recorded video taken during wave flume experiments. The turbulent mixing of air and water, induced by the breaking waves and the runup processes, poses a particular problem for the edge-detection methods, since they rely on a sharp contrast between air and water. In this paper, an alternative method for tracking water surface, based on color segmentation, is presented. A set of experiments were conducted whereby the proposed method was used to detect water surface profiles for various types of breaking waves interacting with a rubble mound breakwater. The results were further processed to compute the surface velocity during runup. The time-history of surface velocity is shown to closely parallel the point measurements taken nearby the instrumented armor unit. These velocities can potentially serve as boundary conditions for determining the dynamic loads exerted on the armour units. Further, the image processing results are used to remove the time-varying buoyant force from the measured force acting on an individual armour unit, providing additional insight into how the forces develop over time.

Visual Measurement of Water Level under Complex Illumination Conditions.

Image-based water level measurement is a visual-sensing technique which automatically inspects the reading of the water line via image processing instead of the human eye. It can be realized easily on an existing video surveillance system and has advantages like low cost, non-contact, as well as results that are verifiable. It has the potential to be widely used in flood and waterlogging monitoring, while facing the challenge that water-line detection under complex natural or artificial illumination conditions is quite difficult in field applications. To handle this problem, a method is proposed assuming that the water line is generally located on the row with the largest local change of gray or edge features in the image of the water gauge. The water line is determined by coarse-to-fine detection of the position of the maximum mean difference (MMD) of the horizontal projections of gray and edge images. Image-based flow-level measurement systems were developed at two measurement sites. In situ comparative experiments were conducted with the float-type stage gauge and other image-based methods. The results show that the fusion of gray and edge features can overcome the shortcomings of single feature methods under complex illumination conditions such as dim light, glares, shadows and artificial night lighting. A coarse-to-fine strategy utilizes the periodicity of the surface pattern distribution of the standard bicolor water gauge, which improves the reliability of water-line detection. The resolution and accuracy of water-level measurement are 1 mm and 1 cm, respectively. In particular, the MMD value is efficient at identifying extremely unfavorable conditions and reducing gross errors.

Novel background calibration algorithm for image in non-uniform illumination field

For the purpose of solving the high quality required in some image based measurement systems, a new calibration algorithm for a non-uniform illumination field image is proposed on the basis of some existing algorithm. In this algorithm, by analysing the characteristics of the potential function for target detection, a new potential function for target detection was designed. A measurement function for standardisation of variety was deduced thereafter. After that, the mapping function from the original image to the background calibration image was given. Numerical simulations showed that the proposed algorithm can restrain the non-uniform background illumination field and calibrate the strong fluctuant background of the illumination field image and thus improve the quality of the image. Meanwhile, the algorithm is simple to carry out and very suitable in practice.

Integration of close range photogrammetry and expert system capabilities in order to design and implement optical image based measurement systems for intelligent diagnosing disease

In medical applications and disease diagnosis devices, image is considered as a tool for measurement and data acquisition. Most of the imaging methods usually used in medical applications are invasive and have several side effects on human body. So, other types of image based measurement systems should be developed for medical applications. The systems must be able to use the images captured in visible part of the electromagnetic spectrum. In this research a new image based disease diagnosis method has been developed which uses optical images for measuring required symptoms. In the systems which are implanted based on the suggested method measurement capabilities of close range photogrammetry and decision making ability of expert system are integrated. The integrated system can be used for the diseases whose symptoms are visible or appear as deformations out of body and around the affected area. For evaluation of the suggested method, an integrated system has been designed and implemented for intelligent diagnosing foot deformity.

Multi-exposure imaging for measurements in rubber production

In the paper, the application of high dynamic range and exposure fusion techniques to image-based measurement systems is described. The advantages of such techniques are discussed, and their performances are compared to the original high-contrast images and between them. Results will show the improvements of measurement reliability achieved with the technique presented in the case of length measurements of industrial products characterized by different surface reflectance.

Representation of homogeneous translucent materials using the P3 approximation and an image-based bidirectional subsurface scattering reflectance distribution function measurement system

In computer graphics applications, the standard diffusion model (SDA) is used to represent translucent materials. However, the SDA is not suitable for the representation of the translucent materials with weakly scattering properties. We represent the translucent materials with the weakly scattering properties by using the P3 approximation, since the P3 approximation can more accurately represent such translucent materials than the SDA. We also present an efficient and stable image-based bidirectional subsurface scattering reflectance distribution function measurement system that can measure the reflectance property of homogeneous translucent materials. From the high-dynamic-range image of a translucent material acquired from the proposed image-based measurement systems, the reduced scattering and the absorption coefficients of the material are estimated to represent its translucent property in computer graphics applications. We demonstrate the strength of the P3 approximation for representing the translucent materials using various examples with realistic illumination based on an environmental map.

Camera Calibration Using Neural Network for Image-Based Soil Deformation Measurement Systems

Abstract A neural network camera calibration algorithm has been adapted for image-based soil deformation measurement systems. This calibration algorithm provides a highly accurate prediction of object data points from their corresponding image points. The experimental setup for this camera calibration algorithm is rather easy, and can be integrated into particle image velocimetry (PIV) to obtain the full-field deformation of a soil model. The performance of this image-based measurement system was illustrated with a small-scale rectangular footing model. This fast and accurate calibration method will greatly facilitate the application of an image-based measurement system into geotechnical experiments.

Performance of a 2D image-based anthropometric measurement and clothing sizing system

Two-dimensional, image-based anthropometric measurement systems offer an interesting alternative to traditional and three-dimensional methods in applications such as clothing sizing. These automated systems are attractive because of their low cost and the speed with which they can measure size and determine the best-fitting garment. Although these systems have appeal in this type of application, not much is known about the accuracy and precision of the measurements they take. In this paper, the performance of one such system was assessed. The accuracy of the system was analyzed using a database of 349 subjects (male and female) who were also measured with traditional anthropometric tools and techniques, and the precision was estimated through repeated measurements of both a plastic mannequin and a human subject. The results of the system were compared with those of trained anthropometrists, and put in perspective relative to clothing sizing requirements and short-term body changes. It was concluded that image-based systems are capable of providing anthropometric measurements that are quite comparable to traditional measurement methods (performed by skilled measurers), both in terms of accuracy and repeatability.