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Camera sensor arrangement for crop/weed detection accuracy in agronomic images.

Romeo J, Guerrero JM, Montalvo M, Emmi L, Guijarro M, Gonzalez-de-Santos P, Pajares G - Sensors (Basel) (2013)

Bottom Line: In Precision Agriculture, images coming from camera-based sensors are commonly used for weed identification and crop line detection, either to apply specific treatments or for vehicle guidance purposes.Accuracy of identification and detection is an important issue to be addressed in image processing.There are two main types of parameters affecting the accuracy of the images, namely: (a) extrinsic, related to the sensor's positioning in the tractor; (b) intrinsic, related to the sensor specifications, such as CCD resolution, focal length or iris aperture, among others.

View Article: PubMed Central - PubMed

Affiliation: Department of Software Engineering and Artificial Intelligence, Faculty of Informatics, Complutense University, Madrid 28040, Spain. jromeo99@hotmail.com

ABSTRACT
In Precision Agriculture, images coming from camera-based sensors are commonly used for weed identification and crop line detection, either to apply specific treatments or for vehicle guidance purposes. Accuracy of identification and detection is an important issue to be addressed in image processing. There are two main types of parameters affecting the accuracy of the images, namely: (a) extrinsic, related to the sensor's positioning in the tractor; (b) intrinsic, related to the sensor specifications, such as CCD resolution, focal length or iris aperture, among others. Moreover, in agricultural applications, the uncontrolled illumination, existing in outdoor environments, is also an important factor affecting the image accuracy. This paper is exclusively focused on two main issues, always with the goal to achieve the highest image accuracy in Precision Agriculture applications, making the following two main contributions: (a) camera sensor arrangement, to adjust extrinsic parameters and (b) design of strategies for controlling the adverse illumination effects.

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Related in: MedlinePlus

Dependency of the number of pixels (n) against h, d and α.
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f6-sensors-13-04348: Dependency of the number of pixels (n) against h, d and α.

Mentions: Results in Table 1 are graphically displayed in Figure 6 for convenience and better visibility, with the 125 values obtained for n. As we can see from the graph, there are five sets of five values each (marked with a red circle) that correspond to the maximum values of n. All these values were obtained at the distance of 3 meters which leads us to the first conclusion of our study (a quite intuitive but perhaps not obvious one): “The closer the ROI is from our camera the higher the resolution and therefore the accuracy on weeds and crop lines detection”.


Camera sensor arrangement for crop/weed detection accuracy in agronomic images.

Romeo J, Guerrero JM, Montalvo M, Emmi L, Guijarro M, Gonzalez-de-Santos P, Pajares G - Sensors (Basel) (2013)

Dependency of the number of pixels (n) against h, d and α.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3673087&req=5

f6-sensors-13-04348: Dependency of the number of pixels (n) against h, d and α.
Mentions: Results in Table 1 are graphically displayed in Figure 6 for convenience and better visibility, with the 125 values obtained for n. As we can see from the graph, there are five sets of five values each (marked with a red circle) that correspond to the maximum values of n. All these values were obtained at the distance of 3 meters which leads us to the first conclusion of our study (a quite intuitive but perhaps not obvious one): “The closer the ROI is from our camera the higher the resolution and therefore the accuracy on weeds and crop lines detection”.

Bottom Line: In Precision Agriculture, images coming from camera-based sensors are commonly used for weed identification and crop line detection, either to apply specific treatments or for vehicle guidance purposes.Accuracy of identification and detection is an important issue to be addressed in image processing.There are two main types of parameters affecting the accuracy of the images, namely: (a) extrinsic, related to the sensor's positioning in the tractor; (b) intrinsic, related to the sensor specifications, such as CCD resolution, focal length or iris aperture, among others.

View Article: PubMed Central - PubMed

Affiliation: Department of Software Engineering and Artificial Intelligence, Faculty of Informatics, Complutense University, Madrid 28040, Spain. jromeo99@hotmail.com

ABSTRACT
In Precision Agriculture, images coming from camera-based sensors are commonly used for weed identification and crop line detection, either to apply specific treatments or for vehicle guidance purposes. Accuracy of identification and detection is an important issue to be addressed in image processing. There are two main types of parameters affecting the accuracy of the images, namely: (a) extrinsic, related to the sensor's positioning in the tractor; (b) intrinsic, related to the sensor specifications, such as CCD resolution, focal length or iris aperture, among others. Moreover, in agricultural applications, the uncontrolled illumination, existing in outdoor environments, is also an important factor affecting the image accuracy. This paper is exclusively focused on two main issues, always with the goal to achieve the highest image accuracy in Precision Agriculture applications, making the following two main contributions: (a) camera sensor arrangement, to adjust extrinsic parameters and (b) design of strategies for controlling the adverse illumination effects.

Show MeSH
Related in: MedlinePlus