Camera-based systems

At the production line in question, the profiles surface quality and cross-section geometry deviation was already analyzed and recorded by online optical quality inspection systems. These camera based systems usually mark defective profile sections visibly, to separate them out for the operating personnel [910]. In some cases, this data was analyzed to quantify the amount and kind of failures statistically to control the rate of production faults. For an integrated management of process, user interaction, and fault information, and quantitative quality data, the records of these inspection systems also had to be integrated. 

Automated inspection is performed by light transmission and camera-based systems. This process decreases human contact with the packaging component. Compared with manual inspection, an automated vial inspectirMi process is more consistent and can be more cost-effective over a longer time period of use. 

Against the backdrop of recent technical developments in modem driver assistance systems, a variety of camera-based systems have been introduced in series production vehicles. The realized functions range from simple rear-view cameras to advanced 360° surround view systems and even night-vision assistance systems including object recognition and sensor fusion. As a mle, such systems offered in series production vehicles are considered to be comfort or assistance systems and cannot be considered as mandatory vehicle systems. ISO 16505 2015, however, focuses on camera monitor systems which are intended to replace systems that are mandatory under current law. 

Since TIRF produces an evanescent wave of typically 80 nm depth and several tens of microns width, detection of TIRF-induced fluorescence requires a camera-based (imaging) detector. Hence, implementing TIRF on scanning FLIM systems or multiphoton FLIM systems is generally not possible. To combine it with FLIM, a nanosecond-gated or high-frequency-modulated imaging detector is required in addition to a pulsed or modulated laser source. In this chapter, the implementation with of TIRF into a frequency-domain wide-field FLIM system is described. 

Zheng, W., Carroll, S.S., Inglese, J., Graves, R., Howells, L., and Strulovici, B., Miniaturization of a hepatitis C virus RN A polymerase assay using a — 102°C cooled CCD camera-based imaging system, Anal. Biochem., 290,214, 2001. 

Uschold A 2002 Scientific Test Report Current Capabilities of Digital Cameras and the Comparison of the Classical Architecture of Digital Cameras based on 35mm SLR-Systems and a Digital Optimized Architecture. Scientific Test Report, Anders Uschold Digitaltechnik, Munich, Germany. 

Fig. 23 Scheme showing the components of a CCD camera-based imaging system for the read-out microarrays (Applied Precision, Issaquah, Wash. [142])... 

Theoretically, CCD s offered the most attractive features of the remaining choices, photodiodes and CCD s. However, at the time when the decision had to be made, CCD technology was, and still is, too much in flux, for their use in a mass spectrometer system and too higji in cost to be a reasonable choice. The cost factor would be amplified even further when one considers the increased requirements on the data acquisition system due to the 60-fold increase in data rate ( 860,00 vs 14,300 ) data points per spectrum. These and other considerations led to the decision to implement the second generation detector with a photodiode (Reticon) based camera. This system is now in operation producing excellent data and will be described in detail in the following section. 

In present common scenario, sorting and grading of fruit according to maturity level are performed manually before transportation. This manual sorting by visual inspection is labor intensive, time consuming and suffers from the problem of inconsistency and inaccuracy in judgment by different human. Which creates a demand for low cost exponential reduction in the price of camera and computational facility adds an opportunity to apply machine vision based system to assess this problem. 

Here the proposed technique applies machine vision based system to predict the maturity level and size of mango from its RGB image frame, collected with the help of a CCD camera. In additions, the method can be extended and applied to analyze and extract the visual properties of other agricultural products as well. The materials and methods, details preprocessing of image, different feature extraction methods and the basic theory of GMM are discussed in the following sections. Finally the results, discussions and conclusions are summarized at the last section. 

Test has been conducted for the five varieties of mango fruit only, but can be extended for other fruits where there are reasonable changes in skin color texture occur with maturity. The variations of classification performances with the variation of other factors like changes in ambient light, camera resolution, and distance of the camera were not studied. The study shows that, machine vision based system performance, is closer to the manual experts, where experts judge the mangoes maturity level not only by the skin color but also with firmness and smell. 

Fourier domain OCT measures interference fringes in the spectral separated domain either by a spectrometer with a high-speed line-scan camera (Fig. 2) or a swept laser source-based system that uses a single detector [3, 6, 8]. Modulation of the interference fringe intensity in the spectral domain is used to determine the location... 

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