Detecting contour saliences using tensor scale

14th IEEE International Conference on Image Processing (ICIP), San Antonio, TX, USA, 2007


Tensor scale is a morphometric parameter that unifies the representation of local structure thickness, orientation, and anisotropy, which can be used in several image processing tasks. This paper introduces a new application for tensor scale, which is the detection of saliences on a given contour, based on the tensor scale orientations computed for the entire object and mapped to its contour. For validation purposes, we present a shape descriptor that uses the detected contour saliences. Experimental results are provided, comparing the proposed method with our previous contour salience descriptor (CS). We show that the proposed method can be not only faster and more robust in the detection of salience points than the CS method, but also more effective as a shape descriptor.


    authors      = “Fernanda A. Andal{\‘o} and Paulo A. V. Miranda and Ricardo da S. Torres and Alexandre X. Falc{~a}o”,
    title        = “Detecting contour saliences using tensor scale”,
    booktitle    = “14th {IEEE} International Conference on Image Processing ({ICIP})”,
    number       = 6,
    pages        = “349–352”,
    year         = 2007,
    address      = “San Antonio, TX, USA”,