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IEICE TRANSACTIONS on Information

Extraction of Glossiness of Curved Surfaces by the Use of Spatial Filter Simulating Retina Function

Seiichi SERIKAWA, Teruo SHIMOMURA

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Summary :

Although the perception of gloss is based on human visual perception, some methods for extracting glossiness, in contrast to human ability, have been proposed involving curved surfaces. Glossiness defined in these methods, however, does not correspond with psychological glossiness perceived by the human eye over the wide range from relatively low gloss to high gloss. In addition, the obtained glossiness in these methods changes remarkably when the curvature radius of the high-gloss object becomes larger than 10mm. In reality, psychological glossiness does not change. These methods, furthermore, are available only for spherical objects. A new method for extracting glossiness is proposed in this study. For the new definition of glossiness, a spatial filter which simulates human retina function is utilized. The light intensity distribution of the curved object is convoluted with the spatial filter. The maximum value Hmax of the convoluted distribution has a high correlation with psychological glossiness Gph. From the relationship between Gph and Hmax, new glossiness Gf is defined. The gloss-extraction equipment consists of a light source, TV camera, an image processor and a personal computer. Cylinders with the curvature radii of 3-30 mm are used as the specimens in addition to spherical balls. In all specimens, a strong correlation, with a correlation coefficient of more than 0.97, has been observed between Gf and Gph over a wide range. New glossiness Gf conforms to Gph even if the curvature radius in more than 10 mm. Based on these findings, it is found that this method for extracting glossiness is useful for the extraction of glossiness of spherical and cylindrical objects over a wide range from relatively low gloss to high gloss.

Publication
IEICE TRANSACTIONS on Information Vol.E77-D No.3 pp.335-342
Publication Date
1994/03/25
Publicized
Online ISSN
DOI
Type of Manuscript
PAPER
Category
Image Processing, Computer Graphics and Pattern Recognition

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