Machine vision applications -  Successful examples from many industries


Successful examples from many industries

Baked product inspection

Crumb is a term that bakers use to define the inside of bread and other baked products. By looking at the way the crumb cell structure is formed, and the shape and size and colour of the cells, a baker can analyze the hydration, flour types, and yeast amounts as well as how the dough was mixed and shaped. The shape and crust can reveal how the bread was baked, flour types used, fermentation balance, and moulding techniques. Image analysis is a powerful way of analyzing crumb cell distribution and the shape of bread products.

STEMMER IMAGING has redeveloped the imaging system for the C-Cell bread & baked product quality assessment system manufactured by Calibre Control International Ltd. C-Cell produces images of crumb cell structure and distribution in baked products such as breads, buns, pastries, cakes, snack foods, pizza and even extruded products. Originally developed in prototype form by Campden BRI, C-Cell was commercialised by Calibre Control International Ltd. When Campden BRI decided it could no longer provide software support for the product, STEMMER IMAGING not only took over support for the code but also completely revised the machine vision configuration used.

The images of the crumb cells show the number of cells, cell area and wall thickness and any holes can be identified and quantified in relation to the cell structure. An image is analysed to provide 48 data values and 5 processed images showing particular features of the sample. Cell distribution patterns can also be identified and the data will reveal cell elongation, circulation and other volume contours. The analysis requires high quality images to be produced reliably and repeatably, with sufficient image contrast to allow the measurements to be made. Data and images are saved to a database for subsequent review, data manipulation and reporting.

STEMMER IMAGING completely transformed the image acquisition process within the C-Cell instrument by using the popular GigE Vision imaging standard, improved illumination and updated control code. It established a hardware independence that removes the need to use a given component from any one supplier, while providing the flexibility for future developments.