To improve the accuracy of fringe projection profilometry for a single deformed pattern, an instantaneous phase retrieval method is proposed using a wavelet ridge section and an adaptive bandpass filter based on dyadic wavelets. First, we present a concept and assumption named wavelet ridge section to depict the instantaneous phases of the deformed fringe signals, which are also degraded by noise, and then introduce a formula to calculate the width of the wavelet ridge section. Furthermore, an adaptive bandpass filter is designed for extracting the wavelet subsignals corresponding to the wavelet ridge sections to reconstruct the analytical signal. Finally, the instantaneous phase of the distorted fringe pattern is effectively retrieved. All parameters of our method are designed to be adaptive for different fringe patterns. Our experiments indicate that the proposed method is effective for measurements and outperforms other existing mainstream wavelet transform profilometry techniques, not only in accuracy but also in noise suppression performance.
We present an innovative calibration method for line-scan cameras to estimate the intrinsic parameters. The calibration involves using a stationary planar pattern that consists of repeated vertical and slanted lines, and constructing a two-dimensional (2-D) calibration framework with one-dimensional (1-D) data. A feature point reconstruction method is applied to transform the 1-D camera calibration problem into the 2-D scope. Camera parameters are then solved by using a 2-D camera model with constraints unique to 1-D geometry. In our tests over 12 calibrations with images of 2048×2048 pixels , the average of the reprojection errors is 0.46 pixels. As opposed to other line-scan camera calibration techniques, this method does not require the camera to progressively scan a pattern, thus eliminating the need for additional mechanical devices to assist the calibration. This method does not need a three-dimensional pattern as a calibration target, either. The stationary planar target makes the calibration more suitable for an application that has to be done in a nonlaboratory setting, such as highway pavement inspection.
The increasing prevalence of obesity suggests a need to develop a convenient, reliable, and economical tool for assessment of this condition. Three-dimensional (3-D) body surface imaging has emerged as an exciting technology for the estimation of body composition. We present a new 3-D body imaging system, which is designed for enhanced portability, affordability, and functionality. In this system, stereo vision technology is used to satisfy the requirement for a simple hardware setup and fast image acquisition. The portability of the system is created via a two-stand configuration, and the accuracy of body volume measurements is improved by customizing stereo matching and surface reconstruction algorithms that target specific problems in 3-D body imaging. Body measurement functions dedicated to body composition assessment also are developed. The overall performance of the system is evaluated in human subjects by comparison to other conventional anthropometric methods, as well as air displacement plethysmography, for body fat assessment.
Rutting and pothole are the common pavement distress problems that need to be timely inspected and
repaired to ensure ride quality and safe traffic. This paper introduces a real-time, automated inspection system
devoted for detecting these distress features using high-speed transverse scanning. The detection principle is based
on the dynamic generation and characterization of 3D pavement profiles obtained from structured light
measurements. The system implementation mainly involves three tasks: multi-view coplanar calibration, sub-pixel
laser stripe location, and pavement distress recognition. The multi-view coplanar scheme was employed in the
calibration procedure to increase the feature points and to make the points distributed across the field of view of the
camera, which greatly improves the calibration precision. The laser stripe locating method was implemented in four
steps: median filtering, coarse edge detection, fine edge adjusting, stripe curve mending and interpolation by cubic
splines. The pavement distress recognition algorithms include line segment approximation of the profile, searching
for the feature points, and parameters calculations. The parameter data of a curve segment between two feature
points, such as width, depth and length, were used to differentiate rutting, pothole, and pothole under different
constraints. The preliminary experiment results show that the system is capable of locating these pavement
distresses, and meets the needs for real-time and accurate pavement inspection.
The increasing prevalence of obesity suggests a need to develop a convenient, reliable and economical tool for
assessment of this condition. Three-dimensional (3D) body surface imaging has emerged as an exciting technology
for estimation of body composition. This paper presents a new 3D body imaging system, which was designed for
enhanced portability, affordability, and functionality. In this system, stereo vision technology was used to satisfy the
requirements for a simple hardware setup and fast image acquisitions. The portability of the system was created via
a two-stand configuration, and the accuracy of body volume measurements was improved by customizing stereo
matching and surface reconstruction algorithms that target specific problems in 3D body imaging. Body
measurement functions dedicated to body composition assessment also were developed. The overall performance of
the system was evaluated in human subjects by comparison to other conventional anthropometric methods, as well
as air displacement plethysmography, for body fat assessment.
This paper introduces a high-resolution 3-D scanning system for objective evaluation of fabric fuzziness using laser range-sensing technology. This system consists of a laser range sensor, a 2-D mechanical stage, and a computer with dedicated software. The paper covers the process of surface digitization from 3-D scanning, image-processing techniques for surface feature description, and methods for characterization of fabric fuzziness. It also reports a preliminary test on a set of fabrics that were treated in different laundering cycles to gain different levels of fuzziness. The test demonstrates that this system has great potential for discriminating among fabric fuzziness levels in a quantitative and reliable manner.