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Machine Vision System (machine + vision_system)

Distribution by Scientific Domains
Chemistry75%

Selected Abstracts

Machine Vision Analysis of Antibrowning Potency for Oxalic Acid: A Comparative Investigation on Banana and Apple

JOURNAL OF FOOD SCIENCE, Issue 6 2004
R. Yoruk
ABSTRACT: Relative antibrowning potency of oxalic acid on banana and apple slices was investigated using a machine vision system. Degree of browning on fresh-cut surfaces was evaluated visually and quantitatively by observing changes of CIE L* values and evaluating temporal changes in color spectra based on experimental variables, oxalic acid concentration, and storage time. Browning inhibition was most prominent on banana and apple slices treated with oxalic acid solutions at concentrations of 60 and 5 mM, respectively. Oxalic acid was a more potent antibrowning agent compared with other structurally related acids. Average residual oxalic acid levels in the tissues for an effective antibrowning activity were measured. [source]

Comparison of Minolta colorimeter and machine vision system in measuring colour of irradiated Atlantic salmon

JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, Issue 4 2009
Yavuz Yagiz
Abstract BACKGROUND: Minolta and machine vision are two different instrumental techniques used for measuring the colour of muscle food products. Between these two techniques, machine vision has many advantages, such as its ability to determine L*, a*, b* values for each pixel of a sample's image and to analyse the entire surface of a food regardless of surface uniformity and colour variation. The objective of this study was to measure the colour of irradiated Atlantic salmon fillets using a hand-held Minolta colorimeter and a machine vision system and to compare their performance. RESULTS: The L*, a*, b* values of Atlantic salmon fillets subjected to different electron beam doses (0, 1, 1.5, 2 and 3 kGy) were measured using a Minolta CR-200 Chroma Meter and a machine vision system. For both Minolta and machine vision the L* value increased and the a* and b* values decreased with increasing irradiation dose. However, the machine vision system showed significantly higher readings for L*, a*, b* values than the Minolta colorimeter. Because of this difference, colours that were actually measured by the two instruments were illustrated for visual comparison. Minolta readings resulted in a purplish colour based on average L*, a*, b* values, while machine vision readings resulted in an orange colour, which was expected for Atlantic salmon fillets. CONCLUSION: The Minolta colorimeter and the machine vision system were very close in reading the standard red plate with known L*, a*, b* values. Hence some caution is recommended in reporting colour values measured by Minolta, even when the ,reference' tiles are measured correctly. The reason for this discrepancy in colour readings for salmon is not known and needs further investigation. Copyright © 2009 Society of Chemical Industry [source]

Aspect graphs for three-dimensional object recognition machine vision systems

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 1 2005
Tatiana Tambouratzis
The purpose of this research is to seek evidence for viewer-centered (especially aspect-graph-based) visual processing in the elementary task of object understanding. Two homologous, bilaterally symmetrical three-dimensional (3-D) objects have been employed that differ in that one is based on parts with flat surfaces and the other on parts with curved surfaces. The following procedure has been followed, separately for each object. In the training (saturated free inspection and manipulation) phase, a location (identical for both objects) of the object is marked with a red strip and the subjects' task is to memorize the object structure as well as the position of the strip. In the test phase, two-dimensional views of the object without the strip are presented and the subjects' task is to determine whether the previously marked location should be visible or invisible in the particular view. Findings have been found consistent with an aspect-graph-based 3-D object representation: (a) the reaction times and errors show characteristic dependencies on viewpoint; (b) a number of views (corresponding to certain aspects and aspect transitions of the aspect graph) consistently produce faster and more accurate recognition; (c) the differences in the aspect graphs of the two objects are reflected in differing patterns of reaction times and errors; furthermore; (d) the subjects impose a standard orientation on the objects, whereby a strong inversion effect is observed; and (e) performance varies in a similar way for both objects as a function of tilt. It is concluded that object understanding is viewpoint dependent, that is, based on a number of views. The characteristics of the views found to be most important for object understanding can be employed for creating efficient 3-D object recognition machine vision systems. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 47,72, 2005. [source]