Stereo vision has emerged as an effective approach for contactless 3-D measurements. This paper presents a methodology for the propagation of the measurement uncertainty through stereo-vision calibration and measurement algorithms, according to international standards. The proposed procedure is compared to the reference statistical procedure for uncertainty evaluation, and the results are presented and discussed. The results proved that the proposed procedure was able to estimate the standard uncertainty even at considerable working distances from the calibrated volume with negligible processing times and far more accurately than the theoretical simplified models commonly adopted.

An original procedure is presented for the calibration of fringe-projection-based 3-D vision systems. The proposed approach estimates both the phase-to-depth and transverse relationships by directly measuring the phase maps for only three planes placed within the calibration volume and then estimating the phase maps for a number of other ldquovirtual planes.rdquo Experimental tests conducted on a fringe projection system show the effectiveness of the proposed procedure.

This paper deals with the metrological characterization of a stereovision-based measurement system for the inspection of automotive rubber profiles in an industrial plant. The characterization of this class of measurement systems introduces new challenges due to both the unavailability of reference measurement instruments and the complexity of the measurement system itself, which does not allow a straightforward application of the standard procedures for uncertainty evaluation. To assign optimum values to a number of design parameters, the followed approach focuses not only on evaluating the total uncertainty but also on analyzing systematic effects and influence quantities.

Early detection of melanoma is one of the greatest challenges of dermatologic practice today. A new diagnostic method, the "ELM 7 point checklist", defines a set of seven features, based on color and texture parameters, which describe the malignancy of a lesion. This paper describes image processing algorithms developed for the detection of the occurrence of "Atypical Pigment Network" and "Atypical Vascular Pattern" that are two important criteria of the "7-point checklist" method

Early detection of melanoma is one of the greatest challenges of dermatologic practice today. A new diagnostic method, the "ELM 7 point checklist", defines a set of seven features, based on colour and texture parameters, which describe the malignancy of a lesion. It has been presented as faster and with the same accuracy than the traditional ABCD criteria in the diagnosis of melanoma. In this paper a new system for automated diagnosis of melanocytic skin lesions, based on ELM 7 point checklist, is introduced.