Hrvoje Glavaš

Thermography is probably the most used method of measuring surface temperature by analyzing radiation in the infrared part of the spectrum which accuracy depends on factors such as emissivity and reflected radiation. Contrary to popular belief that thermographic images represent temperature maps, they are actually thermal radiation converted into an image, and if not properly calibrated, they show incorrect temperatures. The objective of this study is to analyze commonly used image processing techniques and their impact on radiometric data in thermography. In particular, the extent to which a thermograph can be considered as an image and how image processing affects radiometric data. Three analyzes are presented in the paper. The first one examines how image processing techniques, such as contrast and brightness, affect physical reality and its representation in thermographic imaging. The second analysis examines the effects of JPEG compression on radiometric data and how degradation of the data varies with the compression parameters. The third analysis aims to determine the optimal resolution increase required to minimize the effects of compression on the radiometric data. The output from an IR camera in CSV format was used for these analyses, and compared to images from the manufacturer’s software. The IR camera providing data in JPEG format was used, and the data included thermographic images, visible images, and a matrix of thermal radiation data. The study was verified with a reference blackbody radiation set at 60 °C. The results highlight the dangers of interpreting thermographic images as temperature maps without considering the underlying radiometric data which can be affected by image processing and compression. The paper concludes with the importance of accurate and precise thermographic analysis for reliable temperature measurement.

One of the main quality characteristics of cereals, especially wheat is its hardness which is closely related with grain’s vitreosity, one of the main quality indicators of a variety. Determination of vitreosity is usually done visually: namely, after the grain is cut with a commercially available grain-cutters, the cut can result in broken or crushed grains which disables the reading and hinders the precision and accuracy. Also, the moment produced from the manual force on the grain-cutter crank, needed to cut the sample of cca. 50 grains placed in the cutter is an average of 30 Nm. Due to the resistance of the grain, yank force appears. This force can cause the whole instrument to be displaced during cutting. To minimize the errors using a commercially available cutter, a new knife/blade has been implemented and tested. The blade of the new knife is turned at the inclination angle of 49° in relation to the cutting objects (grains). This design solution enables achievement of the grain “cutting”, not grain “tearing”, as observed with the existing commercial design solution. With the proposed new design solution, amount of the moment is reduced to 2.72 Nm and the yank force is completely avoided. Also, a significantly lower amount of the cutting force, on the knife blade is achieved. The results obtained with the new knife gave a better read, were more precise, and the gadget was easier to operate since it demanded lower force to cut the grains. The novelty introduced by this research provided better and more reliable insight into determining the vitreousness of grains. Providing a clearer cut and better readability, this solution goes beyond the current literature by reducing the force required for analysis and speeding up the analysis process.