2,504 research outputs found

    A high-resolution full-field range imaging system

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    There exist a number of applications where the range to all objects in a field of view needs to be obtained. Specific examples include obstacle avoidance for autonomous mobile robots, process automation in assembly factories, surface profiling for shape analysis, and surveying. Ranging systems can be typically characterized as being either laser scanning systems where a laser point is sequentially scanned over a scene or a full-field acquisition where the range to every point in the image is simultaneously obtained. The former offers advantages in terms of range resolution, while the latter tend to be faster and involve no moving parts. We present a system for determining the range to any object within a camera's field of view, at the speed of a full-field system and the range resolution of some point laser scans. Initial results obtained have a centimeter range resolution for a 10 second acquisition time. Modifications to the existing system are discussed that should provide faster results with submillimeter resolution

    Toward-1mm depth precision with a solid state full-field range imaging system

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    Previously, we demonstrated a novel heterodyne based solid-state full-field range-finding imaging system. This system is comprised of modulated LED illumination, a modulated image intensifier, and a digital video camera. A 10 MHz drive is provided with 1 Hz difference between the LEDs and image intensifier. A sequence of images of the resulting beating intensifier output are captured and processed to determine phase and hence distance to the object for each pixel. In a previous publication, we detailed results showing a one-sigma precision of 15 mm to 30 mm (depending on signal strength). Furthermore, we identified the limitations of the system and potential improvements that were expected to result in a range precision in the order of 1 mm. These primarily include increasing the operating frequency and improving optical coupling and sensitivity. In this paper, we report on the implementation of these improvements and the new system characteristics. We also comment on the factors that are important for high precision image ranging and present configuration strategies for best performance. Ranging with sub-millimeter precision is demonstrated by imaging a planar surface and calculating the deviations from a planar fit. The results are also illustrated graphically by imaging a garden gnome

    Volume measurement using 3D Range Imaging

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    The use of 3D Range Imaging has widespread applications. One of its applications provides us the information about the volumes of different objects. In this paper, 3D range imaging has been utilised to find out the volumes of different objects using two algorithms that are based on a straightforward means to calculate volume. The algorithms implemented succesfully calculate volume on objects provided that the objects have uniform colour. Objects that have multi-coloured and glossy surfaces provided particular difficulties in determining volume

    Analysis of ICP variants for the registration of partially overlapping time-of-flight range images

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    The iterative closest point (ICP) algorithm is one of the most commonly used methods for registering partially overlapping range images. Nevertheless, this algorithm was not originally designed for this task, and many variants have been proposed in an effort to improve its prociency. The relatively new full-field amplitude-modulated time-of-flight range imaging cameras present further complications to registration in the form of measurement errors due to mixed and scattered light. This paper investigates the effectiveness of the most common ICP variants applied to range image data acquired from full-field range imaging cameras. The original ICP algorithm combined with boundary rejection performed the same as or better than the majority of variants tested. In fact, many of these variants proved to decrease the registration alignment

    Mixed pixel return separation for a full-field ranger

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    Full-field amplitude modulated continuous wave range imagers commonly suffer from the mixed pixel problem. This problem is caused by the integration of light from multiple sources by a single pixel, particularly around the edges of objects, resulting in erroneous range measurements. In this paper we present a method for identifying the intensity and range of multiple return values within each pixel, using the harmonic content of the heterodyne beat waveform. Systems capable of measurements at less than 90 degree phase shifts can apply these methods. Our paper builds on previous simulation based work and uses real range data. The method involves the application of the Levy-Fullagar algorithm and the use of the cyclic nature of the beat waveform to extract the mean noise power. We show that this method enables the separation of multiple range sources and also decreases overall ranging error by 30% in the single return case. Error in the two return case was found to increase substantially as relative intensity of the return decreased

    Multiple return separation for a full-field ranger via continuous waveform modelling

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    We present two novel Poisson noise Maximum Likelihood based methods for identifying the individual returns within mixed pixels for Amplitude Modulated Continuous Wave rangers. These methods use the convolutional relationship between signal returns and the recorded data to determine the number, range and intensity of returns within a pixel. One method relies on a continuous piecewise truncated-triangle model for the beat waveform and the other on linear interpolation between translated versions of a sampled waveform. In the single return case both methods provide an improvement in ranging precision over standard Fourier transform based methods and a decrease in overall error in almost every case. We find that it is possible to discriminate between two light sources within a pixel, but local minima and scattered light have a significant impact on ranging precision. Discrimination of two returns requires the ability to take samples at less than 90 phase shifts

    Extending AMCW lidar depth-of-field using a coded aperture

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    By augmenting a high resolution full-field Amplitude Modulated Continuous Wave lidar system with a coded aperture, we show that depth-of-field can be extended using explicit, albeit blurred, range data to determine PSF scale. Because complex domain range-images contain explicit range information, the aperture design is unconstrained by the necessity for range determination by depth-from-defocus. The coded aperture design is shown to improve restoration quality over a circular aperture. A proof-of-concept algorithm using dynamic PSF determination and spatially variant Landweber iterations is developed and using an empirically sampled point spread function is shown to work in cases without serious multipath interference or high phase complexity

    Illumination waveform optimization for time-of-flight range imaging cameras

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    Time-of-flight range imaging sensors acquire an image of a scene, where in addition to standard intensity information, the range (or distance) is also measured concurrently by each pixel. Range is measured using a correlation technique, where an amplitude modulated light source illuminates the scene and the reflected light is sampled by a gain modulated image sensor. Typically the illumination source and image sensor are amplitude modulated with square waves, leading to a range measurement linearity error caused by aliased harmonic components within the correlation waveform. A simple method to improve measurement linearity by reducing the duty cycle of the illumination waveform to suppress problematic aliased harmonic components is demonstrated. If the total optical power is kept constant, the measured correlation waveform amplitude also increases at these reduced illumination duty cycles. Measurement performance is evaluated over a range of illumination duty cycles, both for a standard range imaging camera configuration, and also using a more complicated phase encoding method that is designed to cancel aliased harmonics during the sampling process. The standard configuration benefits from improved measurement linearity for illumination duty cycles around 30%, while the measured amplitude, hence range precision, is increased for both methods as the duty cycle is reduced below 50% (while maintaining constant optical power)

    Closed-form inverses for the mixed pixel/multipath interference problem in AMCW lidar

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    We present two new closed-form methods for mixed pixel/multipath interference separation in AMCW lidar systems. The mixed pixel/multipath interference problem arises from the violation of a standard range-imaging assumption that each pixel integrates over only a single, discrete backscattering source. While a numerical inversion method has previously been proposed, no close-form inverses have previously been posited. The first new method models reflectivity as a Cauchy distribution over range and uses four measurements at different modulation frequencies to determine the amplitude, phase and reflectivity distribution of up to two component returns within each pixel. The second new method uses attenuation ratios to determine the amplitude and phase of up to two component returns within each pixel. The methods are tested on both simulated and real data and shown to produce a significant improvement in overall error. While this paper focusses on the AMCW mixed pixel/multipath interference problem, the algorithms contained herein have applicability to the reconstruction of a sparse one dimensional signal from an extremely limited number of discrete samples of its Fourier transform

    Understanding and ameliorating non-linear phase and amplitude responses in AMCW Lidar

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    Amplitude modulated continuous wave (AMCW) lidar systems commonly suffer from non-linear phase and amplitude responses due to a number of known factors such as aliasing and multipath inteference. In order to produce useful range and intensity information it is necessary to remove these perturbations from the measurements. We review the known causes of non-linearity, namely aliasing, temporal variation in correlation waveform shape and mixed pixels/multipath inteference. We also introduce other sources of non-linearity, including crosstalk, modulation waveform envelope decay and non-circularly symmetric noise statistics, that have been ignored in the literature. An experimental study is conducted to evaluate techniques for mitigation of non-linearity, and it is found that harmonic cancellation provides a significant improvement in phase and amplitude linearity
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