No abstract

Nowadays, after nearly half a century of rapid and sustained development of light-emitting diodes (LEDs), conventional light sources such as incandescent and fluorescent lamps are beginning to be replaced by LEDs. Therefore, understanding and assessing all the relevant factors that affect the quality of LEDs is becoming increasingly important for design, production and maintenance of various LED products. The most adverse quality-affecting factors are the initial variability of the optical and electrical properties in a batch of LEDs, temperature and electrical dependence and temporal degradation with corresponding variability. In this paper, we survey the most important quality-affecting factors and corresponding methods for their assessment. First, initial variability of the optical and electrical properties in a new batch of LEDs and the corresponding assessment methods are outlined. Next, the temperature stability of optical and electrical properties of LEDs is discussed. Moreover, the most frequently studied methods for spectral degradation and corresponding degradation variability prediction are reviewed according to the accuracy, applicability and specificity. Finally, the advantages and disadvantages of the established models of part stress analysis are pointed out. In this way, all the major factors affecting the quality of LED products are summarized and the corresponding methods for their assessment are outlined.

In this paper we describe a machine vision system for automatic optical quality inspection of light emitting diodes (LEDs). The proposed system is capable of measuring the intensity, mean colour, colour variation, divergence of the optical axis from the mechanical one and viewing angle of the emitted light. These optical properties are obtained by analysing the image of the light projected on a screen. A detailed analysis of the repeatability and thermal stability of the system was performed. The obtained results show that the proposed system is a powerful tool for automatic sorting of LEDs as it is capable of measuring the above-mentioned optical properties with high repeatability.

Abstract. Acquiring near infrared spectra in vivo usually requires a fiber-optic probe to be pressed against the tissue. The applied pressure can significantly affect the optical properties of the underlying tissue, and thereby the acquired spectra. The existing studies consider these effects to be distortions. In contrast, we hypothesize that the pressureinduced spectral response is site-and tissue-specific, providing additional information for the tissue classification. For the purpose of this study, a custom system was designed for dynamic pressure control and rapid acquisition of spectra. The pressure-induced spectral response was studied at three proximate skin sites of the human hand. The diffuse reflectance and scattering were found to decrease with the applied contact pressure. In contrast, the concentrations of chromophores, and consequently the absorption, increased with the applied contact pressure. The pressure-induced changes in the tissue optical properties were found to be site-specific and were modeled as a polynomial function of the applied contact pressure. A quadratic discriminant analysis classification of the tissue spectra acquired at the three proximate skin sites, based on the proposed pressure-induced spectral response model, resulted in a high (90%) average classification sensitivity and specificity, clearly supporting the working hypothesis.

Abstract. Review of the existing studies on the contact pressure-induced changes in the optical properties of biological tissues showed that the reported changes in transmittance, reflectance, absorption, and scattering coefficient are vastly inconsistent. In order to gain more insight into the contact pressure-induced changes observed in biomedical applications involving common probe-spectrometer diffuse reflectance measurement setups and provide a set of practical guidelines minimizing the influence of the changes on the analysis of acquired spectra, we conducted a series of in vivo measurements, where the contact pressure was precisely controlled, and the spectral and contact pressure information were acquired simultaneously. Classification of three measurement sites on a human hand, representing the natural variability in the perfusion and structure of the underlying tissue, was assessed by training and evaluating classifiers at different contact pressure levels and for different probe operators. Based on the results, three practical guidelines have been proposed to avoid classification performance degradation. First, the most suitable pressure level should be identified. Second, the pressure level should be kept in a narrow range during the acquisition of spectra. Third, applications utilizing probes equipped with a calibrated spring can use several classifiers trained at different contact pressure levels to improve classification performance.