A novel technique for identifying elongated shapes in grey-scale images is presented. The method provides the detection and identification of elongated shapes not only modelling their principal direction, but also reconstructing the transversal luminosity profile. The approach is proposed starting from the gradient-weighted Hough transform, endowing the Hough space with more complete information about the luminance gradient of the image. This paper presents and discusses the algorithm devised to implement the method on discretized data. As an example of application, we present results on images from mechanical pieces, where real and false defects are discriminated through effective reconstruction of their luminosity profile.
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