 SPY Grain Grader |
 SPX Speck Expert |
 What's New |
 Company |
 Home Page |
Principles of Image Processing
A general overview of the principles of digital image processing used in the Maztech and Dipix methods are illustrated in the figure at the bottom of the page. The digitization process automatically creates size and color/grey level information.
As a result, image analysis is well suited for two very important analytical functions - size analysis and vision replacement. Size analysis is suited for applications that require quantitative results and can be used in circumstances where a non-destructive method is desired.
Vision replacement is important in applications that demand objective rather than subjective results and in situations that are influenced by human fatigue.
DIA Applied to Grain and Flour Quality
DIA is an established technology that is universally used in the manufacturing and medical industries but is not well understood in grain-based industries outside of research work.
In the grain research community, image analysis was reported as early as 1979 when researchers used the fluorescence image analysis method to differentiate the botanical components of cereal grains based on chemical/spectral variations.
In the late 1980s, researchers used MRI techniques to produce images based on NMR properties of wheat, corn and potatoes.
Many private and public laboratories have imaging systems configured for specific purposes which typically consist of a video camera, frame grabber, illumination mode(s), PC and software suites.
Most systems have been used for predicting grain/flour quality or end-use product quality based on morphological, spectral, physical or chemical parameters. Topics that have been presented and/or published include but are not limited to the following uses:
wheat inspection and grading;
flour refinement using bran content and flour color;
wheat kernel size, color, and morphological variation; bran speck counting in semolina;
sprouting and starch damage in wheat;
water circulation in wheat grains;
soybean seed coat cracking during drying;
moisture profiles and stress cracks in corn kernels during steeping;
monitoring preprocessing efficiency of durum and common wheats;
size distribution of starch granules;
crumb grain and texture evaluation;
opacity and chalkiness of rice;
grading of milled rice;
detection of red-grained wheat;
texture and color analysis for wheat class discrimination;
size/shape discrimination of wheat varieties.
