ABSTRACT

In processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes.

Features

  • Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications

  • Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring

  • Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data

  • Describes the different approaches used during image acquisition, data collection, and visualization

The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives.

section Section I|1 pages

Imaging Systems

chapter Chapter 1|17 pages

Fundamentals

ByP.J. Williams, K. Sendin

chapter Chapter 2|14 pages

Optimization of Hyperspectral Image Cube Acquisition

A Case Study on Meat and Bone Meal
ByCecilia Riccioli, Ana Garrido Varo, Dolores Pérez Marin

chapter Chapter 3|9 pages

Image Segmentation

BySylvio Barbon, Ana Paula Ayub da Costa Barbon, N.A. Valous, D.F. Barbin

chapter Chapter 4|14 pages

Data Extraction and Treatment

ByYao-Ze Feng, Hai-Tao Zhao

section Section II|1 pages

Chemometrics

chapter Chapter 5|23 pages

Multivariate Analysis and Techniques

ByMohammed Kamruzzaman

chapter Chapter 6|23 pages

Principal Component Analysis

ByCristina Malegori, Paolo Oliveri

chapter Chapter 7|6 pages

Partial Least Squares Regression

ByLeo M.L. Nollet

chapter Chapter 8|4 pages

Linear Discriminant Analysis

ByLeo M.L. Nollet

chapter Chapter 9|4 pages

Support Vector Machines

ByLeo M.L. Nollet

chapter Chapter 10|2 pages

Decision Trees

ByLeo M.L. Nollet

chapter Chapter 11|31 pages

Artificial Neural Networks and Hyperspectral Images for Quality Control in Foods

ByLuis Condezo-Hoyos, Wilson Castro

section Section III|2 pages

Applications

chapter Chapter 12|16 pages

Recent Advances for Rapid Detection of Quality and Safety of Fish by Hyperspectral Imaging Analysis

ByChao-Hui Feng, Yoshio Makino, Masatoshi Yoshimura, Francisco J. Rodríguez-Pulido

chapter Chapter 13|19 pages

Applications of Hyperspectral Imaging for Meat Quality and Authenticity

ByMohammed Kamruzzaman

chapter Chapter 14|11 pages

Hyperspectral Imaging

Applications in Analysis of Fruits for Quality and Safety
ByAnoop A. Krishnan, S.K. Saxena

chapter Chapter 15|25 pages

Applications in Vegetables

ByLeo M.L. Nollet, Hong-Ju He, Hui Wang

chapter Chapter 16|6 pages

Applications in Medicinal Herbs and Pharmaceuticals

ByLeo M.L. Nollet, Hong-Ju He, Hui Wang

chapter Chapter 17|5 pages

Hyperspectral Imaging in Dairy Products Analysis

ByBasil K. Munjanja

chapter Chapter 18|9 pages

Hyperspectral Imaging

Application in Quality and Safety of Beverages
ByN.C. Basantia

chapter Chapter 19|14 pages

Raman Hyperspectral Imaging

Application in Food Additives’ Quality and Safety
ByRajesh Kumar R. Singh, N.C. Basantia