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Sensors 2018, 18(2), 429; https://doi.org/10.3390/s18020429

The Impact of Curviness on Four Different Image Sensor Forms and Structures

Department of Technology and Aesthetics, Blekinge Tekniska Högskola, 37141 Karlskrona, Sweden
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Received: 15 December 2017 / Revised: 12 January 2018 / Accepted: 29 January 2018 / Published: 1 February 2018
(This article belongs to the Section Physical Sensors)
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Abstract

The arrangement and form of the image sensor have a fundamental effect on any further image processing operation and image visualization. In this paper, we present a software-based method to change the arrangement and form of pixel sensors that generate hexagonal pixel forms on a hexagonal grid. We evaluate four different image sensor forms and structures, including the proposed method. A set of 23 pairs of images; randomly chosen, from a database of 280 pairs of images are used in the evaluation. Each pair of images have the same semantic meaning and general appearance, the major difference between them being the sharp transitions in their contours. The curviness variation is estimated by effect of the first and second order gradient operations, Hessian matrix and critical points detection on the generated images; having different grid structures, different pixel forms and virtual increased of fill factor as three major properties of sensor characteristics. The results show that the grid structure and pixel form are the first and second most important properties. Several dissimilarity parameters are presented for curviness quantification in which using extremum point showed to achieve distinctive results. The results also show that the hexagonal image is the best image type for distinguishing the contours in the images. View Full-Text
Keywords: software-based; virtual; hexagonal image; grid structure; pixel form; fill factor; curviness quantification; Hessian matrix; critical points software-based; virtual; hexagonal image; grid structure; pixel form; fill factor; curviness quantification; Hessian matrix; critical points
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Wen, W.; Khatibi, S. The Impact of Curviness on Four Different Image Sensor Forms and Structures. Sensors 2018, 18, 429.

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