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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Subpixel Measurement of Living Skin Deformation Using Intrinsic Features
verfasst von : Amir HajiRassouliha, Andrew J. Taberner, Martyn P. Nash, Poul M. F. Nielsen
Erschienen in: Computational Biomechanics for Medicine
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Abstract
Accurate measurement of skin deformation is essential to study and understand its behaviour under mechanical load. Digital image correlation (DIC) techniques are commonly used for in-vivo subpixel measurements of deformation using camera-based devices. However, most of the existing DIC methods have modest accuracy and require the addition of feature-rich textures in order to measure the deformations. These limitations have made it challenging to measure skin deformations using DIC, especially where the skin does not have a rich texture and high measurement accuracies are required. Recently, an accurate and robust algorithm, named phase-based Savitzky–Golay gradient correlation (P-SG-GC), has been proposed for subpixel image registration. This algorithm addresses many of the limitations of existing DIC algorithms, and its advantages could lead to new advances in measuring skin deformations. In this paper, we test the accuracy and applicability of P-SG-GC for measuring subpixel deformations of living skin.
Experiments were performed using a camera, and a flat object attached to a linear translational stage. A series of translational shifts were applied to the object using the linear stage and were measured by P-SG-GC. The result showed that P-SG-GC could successfully estimate translational shifts ranging from 0.05 pixel to larger than 20 pixels (physical shifts from 5 to 2000 μm) in a subimage of 64 × 64 pixel. The standard deviations of the measurements for translational shifts ranged from 0.008 pixel to a maximum of 0.045 pixel in the camera images (i.e. 0.8–4.5 μm). The P-SG-GC algorithm was then used to measure skin deformation over an approximately 100 × 100 mm field-of-view. Results showed that P-SG-GC was capable of measuring skin deformations ranging from subpixel values to more than 19 pixels using only the intrinsic features of skin. The results illustrate that P-SG-GC is a robust, efficient, and accurate algorithm that can significantly improve the methods of measuring deformation distributions of living skin.