Abstract
The paper presents theory and practical aspects of the detectors of characteristic objects in multi-channel images. It is based on the scale-space version of the structural tensor, adapted to operate on multi-channel signals. The method allows for object detection in N(2D signal space with additional respect to the scale-space. Responses of the structural tensor are composed in a linear weighted sum that allows for better signal discrimination. In such a unified tensor framework different feature detectors were defined for detection of lines, corners, lines in the Hough space, structural places, etc. Although the presented method was developed for road sing recognition is can be also used for detection of other regular shapes. The sought objects are defined by a syntactical description of building line segments and their connection type. The paper presents also experimental results and implementation details.
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Cyganek, B. (2005). Object Detection in Multi-channel and Multi-scale Images Based on the Structural Tensor. In: Gagalowicz, A., Philips, W. (eds) Computer Analysis of Images and Patterns. CAIP 2005. Lecture Notes in Computer Science, vol 3691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556121_70
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DOI: https://doi.org/10.1007/11556121_70
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28969-2
Online ISBN: 978-3-540-32011-1
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