Evaluation of Image Analysis Tools for Characterization of Sweet Bread Crumb Structure

Many approaches to evaluate bread crumb features by applying free or at least not too expensive image analysis (IA) software have been published; however, the described procedures showed noticeable differences. The aim of this work was to compare different image scanning resolutions and thresholding...

Full description

Saved in:
Bibliographic Details
Published in:Food and bioprocess technology 2012-02, Vol.5 (2), p.474-484
Main Authors: Farrera-Rebollo, Reynold R., Salgado-Cruz, Ma. de la Paz, Chanona-Pérez, Jorge, Gutiérrez-López, Gustavo F., Alamilla-Beltrán, Liliana, Calderón-Domínguez, Georgina
Format: Article
Language:English
Subjects:
Agriculture
Biotechnology
Bread
Cell density
Chemistry
Chemistry and Materials Science
Chemistry/Food Science
Density
Flour
Food Science
Fractal geometry
Fractals
Image analysis
Image processing
Image segmentation
Original Paper
Scanning
Shape factor
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Many approaches to evaluate bread crumb features by applying free or at least not too expensive image analysis (IA) software have been published; however, the described procedures showed noticeable differences. The aim of this work was to compare different image scanning resolutions and thresholding techniques to quantify sweet bread crumb features (cell density, mean cell area, shape factor) and their relation with fractal dimension. Two sets of experiments were carried out, one to determine the effect of scanning resolution and thersholding method and the other to validate the previous results by evaluating breads with different crumb structures. Nine different scanning resolutions (75, 100, 150, 200, 300, 355, 435, 515, 555 dpi) and two segmentation procedures (Otsu and Manual) were tested. Three different types of commercial sweet breads and a yeasted sweet bread added with different concentrations (six, 12%) of Chia flour ( Salvia hispanica ) were evaluated. Results showed that the percentage of particles with areas between 0.1 and 4.0 mm 2 remained almost constant when using 350 dpi or larger resolution values, while the smallest particles (
ISSN:1935-5130
1935-5149
DOI:10.1007/s11947-011-0513-y