Multi-Spectral Analysis Of Frying Processes For Meat Products |
| | Abstract | This project examines the possibility to assess a number of quality parameters of the frying process for meat using multi-spectral vision technology. The project examines the possibility of creating measures for the frying-treatment of minced beef and diced turkey, and the agglutination of minced beef.
Frying-Treatment Assessment:
It is extremely important to provide adequately processed minced beef and diced turkey to the end customer, among others since under processed meat comes with several health risks. Furthermore it is important to be able to assess the frying-treatment not only as raw and fried, but also based on the quality of the fried meat. E.g. it is important for turkey diced to have an attractive fried surface, but also still to have a juicy kernel.
This project proposes a method for assessment of frying-treatment of the meat contained in an multi-spectral image, based on conventional image analysis and multivariate statistics. This method provides a measure, not only concerning raw or fried meat, but just as well the quality of the fried meat as evaluated by experts. Furthermore the thesis proposes a visualization method, which transforms a multi-spectral image to a RGB image, clearly showing the frying degree of each meat piece / granule contained in the image.
Agglutination of minced beef:
When frying minced beef using the continuous wok, a specially developed method is used to prevent agglutination. This method requires the meat to be frozen, when entered into the wok; if the meat fails to meet this requirement agglutination occurs. Agglutination in fried minced meat is unwanted as high quality minced beef should contain somewhat homogenous sized granules and no large meat lumps. Apart from the visual effects the large lumps can also lead to them being under processed, which obviously is unwanted.
Using the images from each spectral band, a method is proposed creating a number of measures of agglutination from each image. These measures include mean meat granule size, maximum granule size encountered and number of meat granules per cm2. All of these measures have been examined and compared to the physical measure of strainer loss, from which it can be concluded that these can be used as measures of agglutination.
Generally measures are proposed for all quality parameters examined. The proposed methods are not ready for production, as each method should be re-designed for the specific application, but they surely create a basis for future work. I believe this is a step towards the automated frying-process, eliminating the need for constant monitoring by an experienced process operator. | | Type | Master's thesis [Academic thesis] | | Year | 2007 | | Publisher | Informatics and Mathematical Modelling, Technical University of Denmark, DTU | | Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby | | Series | IMM-Thesis-2007-55 | | Note | Supervised by Assoc. Prof. Jens Michael Carstensen, IMM, DTU, and Jens Adler-Nissen, BioCentrum, DTU. | | Electronic version(s) | [pdf] | | BibTeX data | [bibtex] | | IMM Group(s) | Image Analysis & Computer Graphics |
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