1 March 1990 Image Segmentation By Background Extraction Refinements
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Proceedings Volume 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques; (1990) https://doi.org/10.1117/12.969728
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States
Abstract
A segmentation method that refines thresholds that extract the local background is introduced. During the first phase, the method decomposes the image into rectangular regions and measures the left and right standard deviations and graytone mean of each region. Background-homogeneous regions are detected by using criteria based on statistical theory. The background of a homogeneous region is extracted by computing the left and right shoulder thresholds of its graytone distribution from the measured standard deviations and graytone mean of the region. The corresponding thresholds for a non-homogeneous region are computed from estimates of the standard deviations and mean of its background. Pixels are then classified as darker than background, background, or brighter than background. The second phase of the method focuses background extraction refinements in non-homogeneous regions. The statistics of the background classified pixels in each non-homogeneous region are measured. If the set of background classified pixels in a region exhibits homogeneity, background extraction is ameliorated by computing thresholds from the new background statistics. The homogeneity criteria is tightened as the number of background classified pixels in a region decreases. If the set of background classified pixels in a region is non-homogeneous it suggests pixel misclassifications. The final background statistics of the region are then estimated by comparing background statistics measured in two successive trials, and from whether the set of pixels is left or right non-homogeneous, or both. This heuristical approach was implemented by studying non-homogeneous regions in a set of industrial images of moderate complexity. Rules that predict the final background extraction were derived by observing the behavior of successive background statistical measurements in the regions under the presence of dark and/or bright object pixels. Results indicate a significant reduction of background clutter in the industrial scenes. Good results have also been obtained in outdoor scenes of moderate complexity.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arturo A. Rodriguez, Arturo A. Rodriguez, O. Robert Mitchell, O. Robert Mitchell, } "Image Segmentation By Background Extraction Refinements", Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); doi: 10.1117/12.969728; https://doi.org/10.1117/12.969728
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