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Fast Colour Vesselness

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Vesselness in an image is a map that conveys the extent to which certain image structures resemble blood vessels. The standard approach to this problem uses greyscale images. An earlier algorithm [1] derives a vesselness map for a colour image from the Hessian of a pure quaternion whose components are the colour channels. As an alternative to that method, we here divide the vesselness task into two parts: Convert the colour image to a grey image using the Fast Color2Grey algorithm [2, 3], and then use the traditional Frangi Hessian method [4] on that grey image to produce the vesselness map. Compared with the quaternion-based algorithm, the method proposed here is more accurate in identifying retinal blood vessels and also operates 104 times as fast.
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Document Type: Research Article

Publication date: 2011-01-01

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  • CIC is the premier annual technical gathering for scientists, technologists, and engineers working in the areas of color science and systems, and their application to color imaging. Participants represent disciplines ranging from psychophysics, optical physics, image processing, color science to graphic arts, systems engineering, and hardware and software development. While a broad mix of professional interests is the hallmark of these conferences, the focus is color. CICs traditionally offer two days of short courses followed by three days of technical sessions that include three keynotes, an evening lecture, a vibrant interactive (poster) papers session, and workshops. An endearing symbol of the meeting is the Cactus Award, given each year to the author(s) of the best interactive paper; there are also Best Paper and Best Student Paper awards.

    Please note: for Purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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