A single-lens stereo vision system employing a biprism placed in front of the camera will generate unusual distortion in the captured image. Different from the typical image distortions due to lenses, this distortion is mainly induced by the thick biprism and appears to be incompatible with existing lens distortion models. A fully constrained and model-free distortion correction method is proposed. It employs all the projective invariants of a planar checkerboard template as the correction constraints, including straight lines, cross-ratio, and convergence at vanishing point, along with the distortion-free reference point as an additional constraint from the system. The extracted sample points are corrected by minimizing the total cost function formed by all these constraints. With both sets of distorted and corrected points, and the intermediate points interpolated by a local transformation, the correction maps are determined. Thereafter, all the subsequent images could be distortion corrected by the correction maps. This method performs well on the distorted image data captured by the system and shows improvements in accuracy on the camera calibration and depth recovery compared with other correction methods.
This paper provides a comprehensive study on the effect of the biprism angle and position on the field-of-view (FOV) of a single-lens biprism-based stereovision system. The image captured by this system consists of subimages that are regarded as virtual images taken by two virtual cameras. The overlapping area in a stereo-image pair constitutes the common FOV. Stereo-correspondence is only possible for objects placed in this common FOV region. A geometrical analysis of this system by tracing the rays enables an enhanced understanding of the system, both qualitatively and quantitatively. First of all, a simple geometrical approach is proposed to predict the type of FOV produced given a fixed biprism angle, α. A dimensionless coefficient, ε, is proposed to describe the different types of FOV. Second, the effect of the translation of biprism in the z- and x-axes on the system’s FOV can also be determined using geometrical analysis. Experiments are conducted to verify the above predictions. Although there are some degrees of quantitative error between the experimental results and theory, the general theoretical trends are largely supported by the results.
We propose a geometrical approach for virtual camera rectification on uncalibrated single-lens stereovision using a biprism. This system is also called a virtual stereovision system, as the image captured can be divided into two which are equivalent to two images captured using two cameras with different perspectives. The proposed method is divided into two parts. The first part is to compute the projection transformation matrix of two virtual cameras based on a unique geometrical ray sketching, which can accurately recover the extrinsic parameters, and the second part is to compute the rectification transformation matrix, which is applied on the images captured using the system. As the geometrical analysis eliminates the complex calibration process and rectification reduces the correspondence searching to one-dimensional, this method provides a simple stereo matching technique for this system. Experimental results are presented to show the effectiveness of the approach.
Some new understanding of a single-lens binocular stereovision system using a biprism (2F filter) is presented. One image captured by this system is divided into two halves and assumed to be one stereo image pair captured by two virtual cameras generated by the biprism. Hence, this system can also be called a virtual stereovision system. Two different approaches to understanding this system are introduced. One approach is based on a camera calibration technique and another is based on a geometrical analysis of ray sketching. Both approaches enable this system to perform depth recovery in a close range like a typical stereovision system. As the approach based on geometrical analysis requires no complex calibration, great implementation and calibration effort can be saved, in contrast with a normal stereovision system. This approach provides a way to build a binocular stereovision system with a simpler implementation but sufficient accuracy. A complete analysis of this system and the related calibration, depth recovery, and experimentation techniques are presented. Experimentation results are presented to prove the effectiveness of both approaches used to understand this system.
Normal stereovision system requires two or more cameras to capture different views of the same scene. One category of technique called single-lens stereovision attracted many researchers interest because of its significant advantages over the normal stereovision setup including compactness, low cost, less system parameters and ease of calibration, etc. In this paper we present some new understanding of a single-lens stereovision system using a biprism (2F filter). Image captured by the real camera with a biprism placed before its lens, is divided into two equal halves. Each half-image is assumed to be captured by one virtual camera. Two related but different approaches of understanding and modeling such a system are introduced: one is based on camera calibration technique and another is based on geometrical analysis. The latter approach provides an interesting way of understanding this system. It does not require complex calibration, and one field point test is sufficient to determine the system once the system is built and pin-hole camera model is used. Thus, great effort on setup and calibration will be saved compared to normal binocular stereovision system. The approach based on geometrical analysis provides a relatively simpler and sufficiently accurate way of building a close range stereovision system.
A series of experiments were conducted in which corrosion of mild steel in dilute hydrochloric acid was measured by the inprocess acoustic emission method as well as the conventional weightloss method. Results indicate that there is a marked correlation between these two methods of corrosion measurement. It is possible to detect the different stages of corrosion namely uniform corrosion nonuniform corrosion and intense localised corrosion based on the observed acoustic emission count rate. The acoustic emission signals emitted from the corrosion activities were of sufficient magnitude to be easily detected by piezoelectric transducers. The results demonstrate that the acoustic emission technique can be used to monitor and predict the rate of corrosion.