300 is determined using the displacement of the geographic location via GPS. Regardless, the positioning system 304 may be used by the computing device 306 to determine the displacement of the camera 62 between image captures. For example, if the camera 62 is mounted to a tool bar of the work machine 300, the computing device 306 may utilize vehicle speed between image captures to determine camera 62 displacement between image captures. Similarly, the computing device 306 may record the geographic location of the camera 62 or the work machine 300 and determine the geographic distance displacement between the image captures.

The camera 62 and positioning system 304 may be communicatively coupled to the computing device 306. Further, the computing device 306 may be communicatively coupled to an output 308. The output 308 may be a visual display in a cab of the work machine 300, an audio device, or a haptic feedback device that may be selectively engaged by the computing device 306 to provide information about the agricultural work machine 300. In yet another embodiment considered herein, the output 308 may be wirelessly transmitted to a remote device to be used by a remote user. In one aspect of this disclosure, the output 308 may provide access to a remote database such as a cloud-based system. The computing device 306 may be, or include, the controller discussed herein. Alternatively, the computing device 306 may be any control module or the like on the agricultural work machine 300. Accordingly, the computing device 306 contemplated herein may be any device capable of analyzing inputs and providing outputs as discussed herein.

The camera 62 may provide image data to the computing device 306 showing the status of the furrow 202 among other things. The positioning system 304 may provide geographic coordinates to the computing device 306 that correspond with the image data provided by the camera 62 such that each image produced by the camera may be associated with a corresponding geographic coordinate to determine the displacement of the camera 62 between each image. Similarly, the positioning system 304 may provide the speed of the agricultural work machine 300 and the corresponding timing of the image capture to the computing device 306. The computing device 306 may also associate the speed provided by the positioning system 304 with a particular image from the camera 62 and the time between corresponding image captures. The illumination source 302 may be selectively controlled by the computing device 306 in one embodiment. In another embodiment, the illumination source 302 may not be controlled by the computing device 306. In yet another embodiment, there may be no illumination source 302 at all.

Referring now to FIG. 4a, one exemplary first image 400 of the furrow 202 as captured from the camera 62 as positioned in FIG. 2 is illustrated. The first image 400 may be processed by the computing device 306 to identify artifacts on the surface of the ground G and within the furrow 202. The artifacts identified by the computing device 306 may be portions of the image having a pixel intensity and color that is different than the surrounding area. More specifically, the computing device 306 may identify artifacts on the top surface of the ground G labelled as “Ta” in FIG. 4. The top surface artifacts Ta may be general debris often found on the topmost surface of the ground G. These top surface artifacts Ta may include rocks, plant debris, soil indentations, or any other distinguishing characteristic that may stand out relative to the surrounding ground G.

The computing device 306 may also identify artifacts along the walls of the furrow 202. These artifacts are labelled as W1a-W4a in FIG. 4a. The wall artifacts W1a-W4a may similarly be any unique identifier that can be determined on the wall of the furrow 202 based on the image provided to the computing device 306 from the camera 62. Accordingly, the wall artifacts W1a-W4a may be rocks, plant debris, soil abnormalities, or any other distinguishing features in the furrow 202 wall.

The computing device 306 may also identify any seeds Sa positioned within the furrow 202 in the first image 400. While the term seed and letter “S” is used herein, the seed Sa could be any commodity distributed from the row planter 14. For example, this disclosure contemplates identifying and monitoring fertilizer distributed in the furrow as well. Alternatively, any material that is selectively positioned in the furrow 202 by the row planter 14 may be considered a seed Sa for the purposes of this disclosure.

Referring now to FIG. 4b, a schematic representation of a second image 402 captured by the camera 62 as positioned in FIG. 2 is illustrated. The second image 402 may have been captured a short period of time after the first image 400 as the row planter 14 travels along the ground G. As such, the second image 402 may capture the same artifacts as discussed herein for the first image 400 but the location of the artifacts within the frame of the second image 402 may be different than the location of the artifacts in the first image 400. More specifically, FIG. 4b illustrates the artifact location from the first image 400 with an “a” and the artifacts from the second image 402 with a “b” to illustrate the movement of the artifacts within the frame of the first and second image 400, 402 as if the second image 402 was overlaid on the first image 400.

Regarding the surface “T” artifacts in FIG. 4b, each artifact may appear to have been displaced by an anticipated distance from the perspective of the camera 62 between the first image artifact Ta and the second image artifact Tb. The displacement of the surface artifacts Ta, Tb may appear consistent across all surface artifacts Ta, Tb because they are all positioned on approximately the same surface plane of the ground G and therefore they are all being consistently displaced from the perspective of the camera 62. As such, a perceived displacement 404 of the Ta, Tb artifacts is consistent across the ground surface G.

The apparent spacing of the artifacts in the wall of the furrow (W1a-W4a, W1b-W4b), however, will yield different results depending on the distance of the wall artifact W from the camera 62. For example, the center of the furrow 202 may be farther from the camera 62 than the sidewall of the furrow 202 close the surface plane of the ground G. In this configuration, the perceived displacement 404 of the wall artifact W between the first image 400 and the second image 402 may depend on the positioning of the wall artifact W in the wall of the furrow 202. More specifically, the wall artifact W1a-W1b may have a perceived displacement 404 that is greater than the wall artifact W2a-W2b between the first and second image 400, 402 because the wall artifact W2a-W2b is spaced farther from the camera 62 than the wall artifact W1a-W1b. Accordingly, in one aspect of this disclosure the computing device 306 may utilize the perceived displacement 404 of the identified artifacts between the first image 400 and the second image 402 to determine the distance of the artifact from the camera 62. Similarly, the distance of the seed Sa, Sb may be determined based on the perceived displacement 404 of the seed while considering the displacement of the camera 62 between image captures.

Referring now to FIG. 5, one example of a logic flowchart 500 to determine furrow geometry and seed position information is illustrated. The logic flowchart 500 may be implemented by the computing device 306 discussed herein. Alternatively, any device capable of receiving and analyzing image data may implement the logic flowchart 500. In box 502, the computing device 306 may obtain image data of the trench or furrow 202. The image data may be captured by the camera 62 discussed herein and contain at least two different images of the open furrow 202 (i.e., the first image 400 and the second image 402). The two different images may be taken by the camera 62 in a preset time sequence relative to one another. The computing device 306 may obtain and store with the image data a timestamp indicating the precise time each image in the image data was captured. Alternatively, or additionally, each image of the image data may be associated with a geographic location.

The computing device 306 may then identify artifacts within each image of the image data obtained in box 502. Artifacts may be those discussed herein for FIGS. 4a-4b. Artifacts may be any pixel intensity patterns that are uniquely identifiable. For example, artifacts may be locations in the image that have high local gradients in pixel intensity values. As discussed herein, artifacts such as rocks, plant debris, soil deformations, seeds, fertilizer and the like can be identified as an artifact by the computing device 306. More specifically, any object that creates a distinguishable feature in the image may be labelled as an artifact by the computing device 306 in box 504.

In one aspect of this disclosure, the at least two images in the image data are compared to one another in box 506 to determine the perceived displacement of the artifact between images. The perceived displacement may be the distance the artifact appears to have moved in the subsequent images. For example, artifact Ta is identified in the first image and the same artifact Tb is identified in the second image.

Further, the perceived displacement of the artifacts relative to the camera from box 506 may be used by the computing device 306 to develop a profile of the trench or furrow 202 based on the image data and the estimated camera displacement in box 508. More specifically, the computing device 306 may determine the displacement of the camera 62 between image captures using any of the methods considered herein. For example, the computing device 306 may determine camera displacement based on average recorded vehicle speeds of the corresponding work machine between image captures along with the relative time between image captures. Alternatively, the computing device 306 may record the geographic location of the camera 62 at the time of each image capture and determine camera displacement based on the geographic coordinates recorded at the corresponding image captures.

Once the displacement of the camera 62 is determined, the displacement of the camera may be applied to a geometric function to identify the geometric location of artifacts and seeds or other commodities identified in the image data. More specifically, the perceived displacement 404 distance of the artifacts between the first image and the second image of the image data may be processed by the geometric function to identify a geometric location of the corresponding artifact from the camera 62. For example, the Ta and Tb artifacts may all be on the ground surface G and therefore have a perceived displacement 404 that is expected for coplanar artifacts. In this orientation, the computing device 306 may analyze the displacement between the artifacts and note that each of the Ta, Tb artifacts have the expected perceived displacement 404 for co-planar artifacts between the first image and the second image and must therefore be on about the same plane at a distance from the camera 62. However, any artifacts identified in the trench or furrow 202 may have a perceived displacement 404 between the first image and the second image that is indicative of their increased distance from the camera 62 compared to the Ta, Tb artifacts. In this orientation, the computing device 306 may identify the smaller perceived displacement 404 between the artifacts in the trench or furrow 202 to indicate the artifacts are farther from the camera then the artifacts on the surface of the ground (i.e., Ta and Tb artifacts).

As the artifacts in the trench or furrow 202 are identified closer to the base of the trench or furrow 202 (i.e., farther from the camera 62), the perceived displacement 404 may be correspondingly less. For example, the perceived displacement 404 between W4a, W4b may be less than the perceived displacement 404 between the Ta, Tb artifacts because the W4a, W4b artifacts are farther from the camera 62 than the Ta, Tb artifacts. However, the perceived displacement 404 of the W4a, W4b may be greater than the perceived displacement 404 of the W2a, W2b artifact that is positioned closer to the valley of the trench or furrow 202 than the W4a, W4b artifact and therefor farther from the camera 62.

Any number of artifacts may be identified in the image data to develop a profile of the trench or furrow 202. As discussed herein, the perceived displacement 404 of each artifact from the first image to the second image may, together with the estimated displacement of the camera itself, be used to determine the distance of that artifact from the camera 62 by the box 506. Accordingly, a plurality of artifacts may be identified on the ground G and in the walls of the trench or furrow 202 to generate a profile of the trench or furrow 202 based on the distances of the artifacts from the camera 62. In this example, the more artifacts identified and tracked by the computing device 306 may provide a more precise profile of the trench or furrow 202.

The term “perceived displacement” refers to the displacement of the artifact from one image captured by the camera 62 to another. As discussed herein, the camera 62 is coupled to the row planter unit 14 in a fixed orientation. Accordingly, as the planter row unit 14 moves along the ground plane 206 of the ground G, the camera 62 maintains substantially the same orientation towards the ground G while moving along the horizontal plane 208. As discussed herein, the “perceived displacement” of the artifact may be different depending on the distance of the artifact from the camera