View at Google Scholar J. Figure 5 shows swinging in the maize field bean of lines traced for two pixels placed at the bottom row of the image. Subscribe to Table of Contents Alerts. This is applied in this work as described below, reducing the computational cost. Identification of blobs in images infested with weeds in maize fields becomes a very difficult task, because weeds and crops under overlapping in localized areas produce wide blobs.

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An a cappella version of the first verse and chorus can be found during a singing contest judged by Janeane Garofalo in the film The Matchmaker. A set of images were available for processing.

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Those 3D positions, determined by means of stereoimage disparity computation, provide the base information to create an elevation map which uses a 2D array with varying intensity to indicate the height of the crop. On the other hand the discrimination of crops and weeds in the image is a very difficult task because their red, green, and blue spectral components display similar values. Archived from the original on 15 August

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An extension of this algorithm could be done to detect those lines with its corresponding computing time cost. The worst performance obtained for HOU can be explained because crops and weeds concentration produces a high density of values, representing peaks, in the cell accumulator.

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It can detect any number of crop lines with any slope converging in a vanishing point. Different brightness due to different weather conditions:

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This approach requires crops with significant heights with respect the ground. The method is robust enough to work under the above-mentioned undesired effects. It is applied to binary images, which are obtained by applying similar technique to the ones explained above, that is, RGB image transformation to grayscale and binzarization [ 3 , 4 , 17 ].