Banana Pseudostem Width Detection Based on Kinect V2 Depth Sensor.

Abstract

This study used Kinect V2 sensor to collect the three-dimensional point cloud data of banana pseudostem and developed an automatic measurement method of banana pseudostem width. The banana plant was selected as the research object in a banana plantation in Fusui, Guangxi. The mobile measurement of banana pseudostem was carried out at a distance of 1 m from the banana plant using the field operation platform with Kinect V2 as the collection equipment. To eliminate the background data and improve the processing speed, a cascade classifier was used to recognize banana pseudostems from the depth image, extract the region of interest (ROI), and transform the ROI into a color point cloud combined with the color image; secondly, the point cloud was sparse by down-sampling; then, the point cloud noise was removed according to the classification of large-scale and small-scale noise; finally, the stem point cloud was segmented along the y -axis, and the difference between the maximum and minimum values in the x -axis direction of each segment was calculated as its horizontal width. The center point of each segment point cloud was used to fit the slope of the stem centerline, and the average horizontal width was corrected to the stem diameter. The test results show that the average measurement error is only 2.7 mm, the average relative error was 1.34%, and the measurement time is only about 300 ms. It could provide an effective solution for the automatic and rapid measurement of stem width of banana plants and other similar plants.

Plant phenotyping relevance

Kinect深度センサーと点群処理により、バナナ偽茎幅を自動・高速測定する手法を開発し、誤差検証も行っており、表現型取得手法が研究の中心である。

Code and data availability

The article describes Kinect V2 data collection of banana pseudostem point clouds and a custom measurement pipeline, but contains no data availability statement, no public dataset deposit, and no code or model release. No public URL is provided anywhere in the supplied blocks, so no paper-specific reproducible asset is

No evidence-backed public reproduction asset is currently recorded.