Paper
19 December 1985 Eye Spacing Measurement for Facial Recognition
Mark Nixon
Author Affiliations +
Abstract
Few approaches to automated facial recognition have employed geometric measurement of characteristic features of a human face. Eye spacing measurement has been identified as an important step in achieving this goal. Measurement of spacing has been made by application of the Hough transform technique to detect the instance of a circular shape and of an ellipsoidal shape which approximate the perimeter of the iris and both the perimeter of the sclera and the shape of the region below the eyebrows respectively. Both gradient magnitude and gradient direction were used to handle the noise contaminating the feature space. Results of this application indicate that measurement of the spacing by detection of the iris is the most accurate of these three methods with measurement by detection of the position of the eyebrows the least accurate. However, measurement by detection of the eyebrows' position is the least constrained method. Application of these techniques has led to measurement of a characteristic feature of the human face with sufficient accuracy to merit later inclusion in a full package for automated facial recognition.
© (1985) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark Nixon "Eye Spacing Measurement for Facial Recognition", Proc. SPIE 0575, Applications of Digital Image Processing VIII, (19 December 1985); https://doi.org/10.1117/12.966515
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CITATIONS
Cited by 91 scholarly publications and 3 patents.
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KEYWORDS
Eye

Sclera

Iris recognition

Hough transforms

Facial recognition systems

Shape analysis

Digital image processing

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