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A clustering approach to corner point analysis in hand drawn images

A clustering approach to corner point analysis in hand drawn images
A clustering approach to corner point analysis in hand drawn images
Drawing tasks are used widely within neuropsychology for the assessment and monitoring of a variety of conditions. Automated assessment of these tasks improves their repeatability and accuracy in use alongside a reduction in trained therapist resource loading. Using images from test responses collected in an assessment of the condition of visuo-spatial neglect, this paper presents a method utilising a standard corner detection routine (SUSAN) to establish the presence and location of corner points within an image of a drawn geometric shape. It is demonstrated that by applying a series of standard clustering systems to these located corners, the accuracy in terms of number and spatial position of corner points found assessed against actual corner position is improved.
940-943
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Fairhurst, Michael
6a82d154-93fe-4657-bcee-934d5c888192
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Fairhurst, Michael
6a82d154-93fe-4657-bcee-934d5c888192

Guest, Richard and Fairhurst, Michael (2002) A clustering approach to corner point analysis in hand drawn images. In International Conference on Pattern Recognition (ICPR2002). pp. 940-943 . (doi:10.1109/ICPR.2002.1048191).

Record type: Conference or Workshop Item (Paper)

Abstract

Drawing tasks are used widely within neuropsychology for the assessment and monitoring of a variety of conditions. Automated assessment of these tasks improves their repeatability and accuracy in use alongside a reduction in trained therapist resource loading. Using images from test responses collected in an assessment of the condition of visuo-spatial neglect, this paper presents a method utilising a standard corner detection routine (SUSAN) to establish the presence and location of corner points within an image of a drawn geometric shape. It is demonstrated that by applying a series of standard clustering systems to these located corners, the accuracy in terms of number and spatial position of corner points found assessed against actual corner position is improved.

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Published date: 11 August 2002

Identifiers

Local EPrints ID: 489411
URI: http://eprints.soton.ac.uk/id/eprint/489411
PURE UUID: ee34c959-d7c0-41a0-9cbb-6826add05589
ORCID for Richard Guest: ORCID iD orcid.org/0000-0001-7535-7336

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Date deposited: 23 Apr 2024 17:17
Last modified: 24 Apr 2024 02:10

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Contributors

Author: Richard Guest ORCID iD
Author: Michael Fairhurst

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