Toudjeu, ITVan Wyk, BJVan Wyk, MAVan Den Bergh, F2009-01-202009-01-202008-06Toudjeu, IT, Van Wyk, BJ, Van Wyk, MA and Van Den Bergh, F. 2008. Global image feature extraction using slope pattern spectra. 5th International Conference on Image Analysis and Recognition (ICIAR), Povoa de Varzim, Portugal, 25-27 June 2008, pp 640-649.http://www.springer.de/comp/lncs/index.htmlhttp://hdl.handle.net/10204/2848The copyright for this contribution is held by SpringerTraditionally, granulometries are obtained using a series of openings or closings with convex structuring elements of increasing size. Granulometries constitute a useful tool for texture and image analysis since they are used to characterize size distributions and shapes [1], [2]. The granulometric analysis of an image results in a signature of the image with respect to the granulometry used which is referred to as a granulometric curve or pattern spectrum. Granulometric curves are used as feature vectors [3] for applications such as segmentation [4] and texture classification [5]. For example [6], granulometries based on openings with squares of increasing size as structuring elements, were used to extract dominant bean diameter from binary images of coffee beans. Granulometries were also used to estimate the dominant width of the white patterns in the X-ray images of welds [7]. Due to the computational load associated with the calculation of granulometries, Vincent [6], building on the work of Haralick et al. [2] and proposed fast and efficient granulometric techniques using linear openings.enPattern SpectraFeature extractionTexture analysisIntegral imageConference PresentationToudjeu, I., Van Wyk, B., Van Wyk, M., & Van Den Bergh, F. (2008). Global image feature extraction using slope pattern spectra. Springer-Verlag Berlin Heidelberg. http://hdl.handle.net/10204/2848Toudjeu, IT, BJ Van Wyk, MA Van Wyk, and F Van Den Bergh. "Global image feature extraction using slope pattern spectra." (2008): http://hdl.handle.net/10204/2848Toudjeu I, Van Wyk B, Van Wyk M, Van Den Bergh F, Global image feature extraction using slope pattern spectra; Springer-Verlag Berlin Heidelberg; 2008. http://hdl.handle.net/10204/2848 .TY - Conference Presentation AU - Toudjeu, IT AU - Van Wyk, BJ AU - Van Wyk, MA AU - Van Den Bergh, F AB - Traditionally, granulometries are obtained using a series of openings or closings with convex structuring elements of increasing size. Granulometries constitute a useful tool for texture and image analysis since they are used to characterize size distributions and shapes [1], [2]. The granulometric analysis of an image results in a signature of the image with respect to the granulometry used which is referred to as a granulometric curve or pattern spectrum. Granulometric curves are used as feature vectors [3] for applications such as segmentation [4] and texture classification [5]. For example [6], granulometries based on openings with squares of increasing size as structuring elements, were used to extract dominant bean diameter from binary images of coffee beans. Granulometries were also used to estimate the dominant width of the white patterns in the X-ray images of welds [7]. Due to the computational load associated with the calculation of granulometries, Vincent [6], building on the work of Haralick et al. [2] and proposed fast and efficient granulometric techniques using linear openings. DA - 2008-06 DB - ResearchSpace DP - CSIR KW - Pattern Spectra KW - Feature extraction KW - Texture analysis KW - Integral image LK - https://researchspace.csir.co.za PY - 2008 T1 - Global image feature extraction using slope pattern spectra TI - Global image feature extraction using slope pattern spectra UR - http://hdl.handle.net/10204/2848 ER -