title: High Throughput Multispectral Image Processing with Applications in Food Science.
abstract: Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.
authors.affiliation: Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food, Biotechnology and Development, Agricultural University of Athens, Athens, Greece.
authors.forename: Panagiotis
authors.initials: P
authors.lastname: Tsakanikas
authors.affiliation: Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food, Biotechnology and Development, Agricultural University of Athens, Athens, Greece.
authors.forename: Dimitris
authors.initials: D
authors.lastname: Pavlidis
authors.affiliation: Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food, Biotechnology and Development, Agricultural University of Athens, Athens, Greece.
authors.forename: George-John
authors.initials: GJ
authors.lastname: Nychas
mesh_terms: D000465:Algorithms; D001331:Automation; D063427:Food Quality; D005524:Food Technology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D012984:Software; D000069558:Unsupervised Machine Learning