features; the principal objective of a pre-processing stage is to segment the region
of interest to finally apply a processing stage that is in charge of recognizing and
interpreting the image, always seeking to make sense to the object of interest of the
images. In addition, having optimal conditions to acquire a good quality image,
permit having a less complex pre-processing algorithm.
According to Davies (2009), several types of food products have been analyzed
through computational vision techniques including cereals and particularly wheat
that has an important role in the food industry. The wheat (Triticum aestivum L.;
Triticum durum), has been one of the main foods for thousands of years, and today
it has the most worldwide economical importance; European countries, India and
China are the main countries that contribute in more proportion to the world wheat
production with 21.28, 17.62, and 12.36 %, respectively (Hawkesford et al. 2013).
At following, a case of study of artificial vision system applied to grain inspections
is presented.
13.2.2 Artificial Vision Systems Applied Grains
In Mexico, irrigated crops are mainly used for wheat growing, which 95 % of the
annual harvest is produced in the autumn–winter season, such graminaceous
represents the 21 % of the national basic grains consumption, second place just
after the corn grain, with a capita consumption per year of 52 kg and industrial
sales volume that will be increasing between 1 and 2 %. The Mexican national
production in 2009 was 4.01 MT with a total value of more than 15 billion USD
(Agrosintesis 2013).
The proper conservation of stored grains and seeds in any worldwide location is
affected by various factors: regional ecology; barn, silo, or warehouse availability;
type and conditions of grain or seed to be stored; storage climate conditions; and
duration of storage, being the latter difficult to be controlled for high volume crops.
A worldwide loss of stored wheat grain between 10 and 15 % is estimated by
Neethirajan et al. (2007); where main causes are: harvesting machines, water
permeability on grain gluten, bugs, spores, fungus among others. One of the most
important factors to be considered in wheat grain storage is the water permeation
on the grain gluten when temperature gradients happen, encouraging the presence
of bugs, mainly Coleoptera, Lepidopterous and microorganisms like Penicillium,
Aspergillus, Alternaria, Fusarium, Cladosporium, and Rhizopus. Serious types of
damages on stored grains are caused by such bugs populations, from its devaluation up to the total loss, from an agricultural, economical, and nutritional point of
view (Oliveira et al. 2013).
Two kinds of grain damage are caused by bugs, being the grain destruction and
consumption by either adult bugs or bugs’ larval states through feeding and oviposition of (Huang et al. 2013a, b). Besides, the economic and nutritional values,
as well as the germination potential of the grain or seeds are decreased due to the
contamination caused by the bug’s excrements and dead bodies. On the other hand,
366
M. S. Acosta-Navarrete et al.
of interest to finally apply a processing stage that is in charge of recognizing and
interpreting the image, always seeking to make sense to the object of interest of the
images. In addition, having optimal conditions to acquire a good quality image,
permit having a less complex pre-processing algorithm.
According to Davies (2009), several types of food products have been analyzed
through computational vision techniques including cereals and particularly wheat
that has an important role in the food industry. The wheat (Triticum aestivum L.;
Triticum durum), has been one of the main foods for thousands of years, and today
it has the most worldwide economical importance; European countries, India and
China are the main countries that contribute in more proportion to the world wheat
production with 21.28, 17.62, and 12.36 %, respectively (Hawkesford et al. 2013).
At following, a case of study of artificial vision system applied to grain inspections
is presented.
13.2.2 Artificial Vision Systems Applied Grains
In Mexico, irrigated crops are mainly used for wheat growing, which 95 % of the
annual harvest is produced in the autumn–winter season, such graminaceous
represents the 21 % of the national basic grains consumption, second place just
after the corn grain, with a capita consumption per year of 52 kg and industrial
sales volume that will be increasing between 1 and 2 %. The Mexican national
production in 2009 was 4.01 MT with a total value of more than 15 billion USD
(Agrosintesis 2013).
The proper conservation of stored grains and seeds in any worldwide location is
affected by various factors: regional ecology; barn, silo, or warehouse availability;
type and conditions of grain or seed to be stored; storage climate conditions; and
duration of storage, being the latter difficult to be controlled for high volume crops.
A worldwide loss of stored wheat grain between 10 and 15 % is estimated by
Neethirajan et al. (2007); where main causes are: harvesting machines, water
permeability on grain gluten, bugs, spores, fungus among others. One of the most
important factors to be considered in wheat grain storage is the water permeation
on the grain gluten when temperature gradients happen, encouraging the presence
of bugs, mainly Coleoptera, Lepidopterous and microorganisms like Penicillium,
Aspergillus, Alternaria, Fusarium, Cladosporium, and Rhizopus. Serious types of
damages on stored grains are caused by such bugs populations, from its devaluation up to the total loss, from an agricultural, economical, and nutritional point of
view (Oliveira et al. 2013).
Two kinds of grain damage are caused by bugs, being the grain destruction and
consumption by either adult bugs or bugs’ larval states through feeding and oviposition of (Huang et al. 2013a, b). Besides, the economic and nutritional values,
as well as the germination potential of the grain or seeds are decreased due to the
contamination caused by the bug’s excrements and dead bodies. On the other hand,
366
M. S. Acosta-Navarrete et al.