782 all rights reserved near infrared (nIr) spectroscopy is a non-invasive, nondestructive, cost-effective and fast method that has a great (commercial) potential in medical technology. a growing interest in applying nIr spectroscopy in medical diagnostics, such as monitoring of skin disorders and endoscopy of the digestive system, has appeared. despite great advances in nIr technology and methodology in recent years, new innovations are needed to meet the upcoming challenges in health care.the objective of this study was to evaluate the applicability of different wavelength selection methods and to find out, whether nIr spectroscopy can be used to detect skin disorders such as sunburn, or erythema, and further, what effects erythema has on the nIr spectra of skin. this information can be used to assess the feasibility of nIr spectroscopy for skin measurements and imaging in the presence of erythema. although erythema is usually observable in the visible band, nIr spectroscopy may enhance early detection and distinguish other inflammations from erythema. Moreover, ultraviolet (uV)-induced erythema is a convenient and controlled way to cause an inflammation, and because nIr spectra are related to the dermal biochemistry, nIr spectroscopy could be used, for example, for on-line monitoring of drug treatments.nIr radiation can penetrate cutaneous tissue, as well as other biological materials, for several millimeters. Hence nIr can detect phenomena that occur in the deeper layers of skin, for example, erythema-related water influx, thickening of the stratum corneum and metabolic changes. usually, however, most of the information of nIr measurement originates from department of electrical engineering and automation, university of Vaasa, faculty on technology, po Box 700, fI-65101 Vaasa, finlandThe acute effects of sun-bathing on the near-infrared absorption spectra of human skin were studied by exposing the shoulders of a male test subject to bright Finnish high summer mid-day sun. The spectra were measured before, immediately after and for several days after exposure. Four different spectral processing and classification methods were applied to the data set to identify differences caused by exposure to the sun. The spectrophotometer and measuring procedure were found to cause some systematic errors, calling for further development, even though they could, to a large extent, be compensated for computationally. Spectral regions indicating ultraviolet radiation-induced erythema were located and the degree of erythema could be predicted correctly but the signal is weak. This paper discusses promising wavelength selection methods to study the dermal effects of exposure to the sun, as well as difficulties and remedies of near infrared spectroscopic measurements of the skin.

Image matching is a common procedure in computer vision. Usually the size of the image template is fixed. If the matching is done repeatedly, as e.g. in stereo vision, object tracking, and strain measurements, it is beneficial, in terms of computational cost, to use as small templates as possible. On the other hand larger templates usually give more reliable matches, unless e.g. projective distortions become too great. If the template size is controlled locally dynamically, both computational efficiency and reliability can be achieved simultaneously. Adaptive template size requires though that a larger template can be sampled anytime.This paper introduces a method to adaptively control the template size in a digital image correlation based strain measurement algorithm. The control inputs are measures of confidence of match. Some new measures are proposed in this paper, and the ones found in the literature are reviewed. The measures of confidence are tested and compared with each other as well as with a reference method using templates of fixed size. The comparison is done with respect to computational complexity and accuracy of the algorithm. Due to complex inter-actions of the free parameters of the algorithm, random search is used to find an optimal parameter combination to attain a more reliable comparison. The results show that with some confidence measures the dynamic scheme outperforms the static reference method. However, in order to benefit from the dynamic scheme, optimization of the parameters is needed.

This paper studies the applicability of genetic algorithms and imaging to measure deformations. Genetic algorithms are used to search for the strain field parameters of images from a uniaxial tensile test. The non-deformed image is artificially deformed according to the estimated strain field parameters, and the resulting image is compared with the true deformed image. The mean difference of intensities is used as a fitness function. Results are compared with a node-based strain measurement algorithm developed by Koljonen et al. The reference method slightly outperforms the genetic algorithm as for mean difference of intensities. The root-mean-square difference of the displacement fields is less than one pixel. However, with some improvements suggested in this paper the genetic algorithm based method may be worth considering, also in other similar applications: Surface matching instead of individual landmarks can be used in camera calibration and image registration. Search of deformation parameters by genetic algorithms could be applied in pattern recognition tasks e.g. in robotics, object tracking and remote sensing if the objects are subject to deformation. In addition, other transformation parameters could be simultaneously looked for.

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Finnish Funding Agency for Technology and Innovation (TEKES) and the industrial partners of the research project Process Development for Incremental Sheet Forming have supported this research.Abstract-A digital image correlation algorithm for strain measurements with some improvements is introduced and tested. A major problem related to strain measurements with spatial resolution is the lack of simple validation of the results as the overall strain given by the test machine is not applicable as a local strain reference estimate. An implicit error estimation approach based on statistical analysis is introduced and applied to an image test set from a uniaxial tensile test of a planar aluminum test piece. The spatial strain sampling frequency and the measurement accuracy and errors are studied, when varying a few parameters of the algorithm. An intra-validation procedure is in turn used to validate the error estimates.Keywords-error estimation, deformation, material engineering, measurements based on image.