Paper
1 May 2003 Quality indexing by machine vision during fermentation in black tea manufacturing
S. Borah, M. Bhuyan
Author Affiliations +
Proceedings Volume 5132, Sixth International Conference on Quality Control by Artificial Vision; (2003) https://doi.org/10.1117/12.515153
Event: Quality Control by Artificial Vision, 2003, Gatlinburg, TE, United States
Abstract
Although the organoleptic method of tea testing has been traditionally used for quality monitoring, an alternative way by machine vision may be advantageous. Although, the three main quality descriptors estimate the overall quality of made-tea, viz., strength, briskness and brightness of tea liquor, the exact colour detection in fermenting process leads to a good quality-monitoring tool. The use of digital image processing technique for this purpose is reported to play an effective role towards the production of good quality tea though it is not the only quality determining parameter. In this paper, it has been tried to compare the contribution of the chemical constituents towards the final product with the visual appearance in the processing stage by imaging. The use of machine intelligence supports the process somewhat invariantly in comparison to the human decision and colorimetric approach. The captured images are processed for colour matching with a standard image database using HSI colour model. The application of colour dissimilarity and perceptron learning for the standard images and the test images is ensured. Moreover, the performance of the system is being tried to correlate with the decision made by the organoleptic panel assigned for the tea testing and chemical test results on the final product. However, it should be noted that the optimized result could be achieved only when the other quality parameters such as withering, flavour (aroma) detection, drying status etc. are properly maintained.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. Borah and M. Bhuyan "Quality indexing by machine vision during fermentation in black tea manufacturing", Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); https://doi.org/10.1117/12.515153
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Cited by 9 scholarly publications.
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KEYWORDS
Machine vision

Manufacturing

Databases

RGB color model

Image processing

Process control

Image quality

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