An adaptive edge detection filter for light stripe projection (LSP) in surface reconstruction

Abstract

The problem of using light stripe projection (LSP) for reconstructing the 3D surface of several objects positioned at different distances from the camera is addressed in this paper. It is shown using LSP for 3D surface reconstruction of objects at different depths can be significantly improved if adaptive edge detection filter is added. The filter is designed as a local dynamic hysteresis thresholding value generator. It adapts knowledge of the wavelet coefficients in a small neighborhood on the row profile and generates the local hysteresis threshold values to detect a meaningful and useful edge. It is then shown how the filter may be designed to recover missing LSP features by using common edge detection technique and how it increases the accuracy and reliability of 3D surface reconstruction. The adaptive edge detection filter is illustrated by the presentation of experimental results obtained using the methods described in the paper. A test outlines the differences between LSP edges detected with the adaptive edge detection filter and edges detected without the filter.

Model-based light stripe detection for indoor navigation

“…It is observed that LSF width function of x coordinates and distance d, expressed in Eq. (18), can properly predict LSF width. Measured LSF width at pixel coordinates (x, y) is shown in Fig.…”

“…(18). It is noteworthy that amplitude, x-axis standard deviation, and y-axis standard deviation of Gaussian function are functions of distance d:…”

“…With w(x, y) defined by applying a specific LSF intensity threshold value to y Z of Eqs. (18) and (19), LSF width at all pixels can be calculated before actual navigation starts. When applying LOG filtering to any pixel (x, y), one can set the base length of LOG operator, that is s of Eq.…”

“…The Scheimpflug condition, well known and used in photography for a long time, provides considerable improvement in the depth-ofview without the loss of intensity (the lens aperture can be kept at maximum). Chang et al [18] focused the middle of camera scene depth and applied 2D wavelet transform. Subsequently, by increasing LSF-related components and decreasing other components in frequency domain, they could enhance defocused LSF.…”

<title>Light Stripe Projection (LSP) position improvement by using an adaptive filter based on polynomial and parabola fitting</title>

“…Curless and Levoy [8] have introduced a new ranging method based on analyzing the time evolution of the structured light reflections to address this problem for a laser stripe range finder. Focus can weaken the stripe information [9].…”