Minimal Geometric Representation and Strawberry Stem Detection

Leonard, Kathryn; Strawbridge, Rebecca; Lindsay, Danika; Barata, R.; Dawson, Matthew; Averion, Lawrence

doi:10.1109/iccsa.2013.29

Cited by 4 publications

(10 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When the star appears on another stem, on the background or anywhere on the strawberry itself, including the calyx, we consider that the picking point has not been successfully selected. For example, in Figure 7(a), the red and yellow stars are on the target stem and so are counted as successful selections, while the blue star on the mulching film will not be regarded as a successful selection 6 . Similarly, in Figure 7(b), only the yellow star represents a successful picking point selection, while in 7(c), none of the methods have detected a suitable picking point since none of the stars fall on the stem of the ripe strawberry.…”

Section: Resultsmentioning

confidence: 99%

“…The triangle is then used to describe the shape of the strawberry, and the stem can be identified from elements that are perpendicular to the base of the triangle. This method has a reported accuracy rate of 71%, which is much higher than the method using the principal axis of inertia (26.9%) on the images tested in [6]. However, this method only pointed out the possible area of stem selection -it outputs a bounding box around what is identified as the stem -and it does not identify the specific stem that was attached to the target strawberry from the others that may be in the background.…”

Section: Related Workmentioning

confidence: 99%

“…[4] reports a success rate for stem detection of 93% when working on images of strawberries with a pure colour background in a laboratory environment. This represents a relatively simple environment in which to perform stem detection, and later work by [6], who used a combination of images taken in the field, and images of strawberries taken from a Google image search, found the approach to be less effective- [6] reports a 26.9% success rate. More recently, [19] introduced a strawberry picking robot which uses the centroid of the strawberry and the axis of symmetry through the centroid to detect the picking point.…”

Section: Related Workmentioning

confidence: 99%

“…The latest work on this topic is [6], already mentioned above in the context of their critique of [4]. [6] investigates a method which is based on the Blum medial skeleton of the strawberry boundary.…”

Section: Related Workmentioning

confidence: 99%

“…[6] investigates a method which is based on the Blum medial skeleton of the strawberry boundary. From the skeleton, three extreme points can be detected as key medial points to generate a triangle.…”

Section: Related Workmentioning

confidence: 99%

See 4 more Smart Citations

Towards Automated Strawberry Harvesting: Identifying the Picking Point

Huang

Wane

Parsons

2017

Towards Autonomous Robotic Systems

View full text Add to dashboard Cite

Abstract. With the decline of rural populations across the globe, much hope is vested in the use of robots in agriculture as a means to sustain food production. This is particularly relevant for high-value crops, such as strawberries, where harvesting is currently very labour-intensive. As part of a larger project to build a robot that is capable of harvesting strawberries, we have studied the identification of the picking point of strawberries -the point that a robot hand should grasp the strawberry -from images of strawberries. We present a novel approach to identify the picking point and evaluate this approach.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

Towards Automated Strawberry Harvesting: Identifying the Picking Point

Huang

Wane

Parsons

2017

Towards Autonomous Robotic Systems

View full text Add to dashboard Cite

show abstract

Skeleton-Based Recognition of Shapes in Images via Longest Path Matching

Bal

Diebold

Chambers

et al. 2015

Association for Women in Mathematics Series

Self Cite

View full text Add to dashboard Cite

We present a novel image recognition method based on the Blum medial axis that identifies shape information present in unsegmented input images. Inspired by prior work matching from a library using only the longest path in the medial axis, we extract medial axes from shapes with clean contours and seek to recognize these shapes within "no isy" images. Recognition consists of matching longest paths

show abstract

Review of Robotic Technology for Strawberry Production

2016

Appl. Eng. Agric

View full text Add to dashboard Cite

With an increasing world population in need of food and a limited amount of land for cultivation, higher efficiency in agricultural production, especially fruits and vegetables, is increasingly required. The success of agricultural production in the marketplace depends on its quality and cost. The cost of labor for crop production, harvesting, and postharvesting operations is a major portion of the overall production cost, especially for specialty crops such as strawberry. As a result, a multitude of automation technologies involving semi-autonomous and autonomous robots have been utilized, with an aim of minimizing labor costs and operation time to achieve a considerable improvement in farming efficiency and economic performance. Research and technologies for weed control, harvesting, hauling, sorting, grading, and/or packing have been generally reviewed for fruits and vegetables, yet no review has been conducted thus far specifically for robotic technology being used in strawberry production. In this article, studies on strawberry robotics and their associated automation technologies are reviewed in terms of mechanical subsystems (e.g., traveling unit, handling unit, storage unit) and electronic subsystems (e.g., sensors, computer, communication, and control). Additionally, robotic technologies being used in different stages in strawberry production operations are reviewed. The robot designs for strawberry management are also categorized in terms of purpose and environment.

show abstract

Minimal Geometric Representation and Strawberry Stem Detection

Cited by 4 publications

References 10 publications

Towards Automated Strawberry Harvesting: Identifying the Picking Point

Towards Automated Strawberry Harvesting: Identifying the Picking Point

Skeleton-Based Recognition of Shapes in Images via Longest Path Matching

Review of Robotic Technology for Strawberry Production

Contact Info

Product

Resources

About