Single Shot High-Accuracy Diameter at Breast Height Measurement with Smartphone Embedded Sensors (2025)

W. Xiang, S. Fei, and S. Zhang, “Single Shot High-Accuracy Diameter at Breast Height Measurement with Smartphone Embedded Sensors,” Sensors, 25(16), 5060 (2025); doi: 10.3390/s25165060

Abstract

Tree diameter at breast height (DBH) is a fundamental metric in forest inventory and management. This paper presents a novel method for DBH estimation using the built-in light detection and ranging (LiDAR) and red, green and blue (RGB) sensors of an iPhone 13 Pro, aiming to improve measurement accuracy and field usability. A single snapshot of a tree, capturing both depth and RGB images, is used to reconstruct a 3D point cloud. The trunk orientation is estimated based on the point cloud to locate the breast height, enabling robust DBH estimation independent of the capture angle. The DBH is initially estimated by the geometrical relationship between trunk size on the image and the depth of the trunk. Finally, a pre-computed lookup table (LUT) is employed to improve the initial DBH estimates into accurate values. Experimental evaluation on 294 trees within a capture range of 0.25 m to 5 m demonstrates a mean absolute error of 0.53 cm and a root mean square error of 0.63 cm.

"Auto-focusing and auto-exposure method for real-time structured-light 3D imaging" (2025)

L. Chen, Y. Yang and S. Zhang, “Auto-focusing and auto-exposure method for real-time structured-light 3D imaging,“ Optical Engineering 64(4), 044105 (2025), doi: 10.1117/1.OE.64.4.044105

Abstract

This paper presents a method that automatically adjusts focus setting and exposure time for real-time structured-light three-dimensional (3D) imaging. The proposed method first reconstructs a rough 3D shape using three phase-shifted low-frequency fringe patterns. Then, the camera focal length and corresponding exposures are tuned to focus the measured object with proper exposure from the rough 3D measurement. Experimental results demonstrated the effectiveness of the proposed method for real-time dynamic 3D shape measurements within a depth range of approximately 455 mm to 893 mm.

"Combining multispectral and high-resolution 3D imaging for leaf vein segmentation and density measurement,“ (2025)

.-H. Liao and S. Zhang, “Combining multispectral and high-resolution 3D imaging for leaf vein segmentation and density measurement,“ Frontiers in Plant Science, (2025)

Abstract

Accurate leaf vein segmentation and vein density (VLA) measurement are crucial for understanding plant physiology. Traditional 2D imaging techniques often require labor-intensive and destructive processes, such as leaf flattening or chemical clearing, thereby limiting their practicality for high-throughput applications. In this study, we present a novel framework that integrates multispectral and high-resolution 3D imaging to enhance leaf vein segmentation and VLA measurement. By leveraging digital fringe projection, our system captures grayscale, multispectral, and 3D topographical data within a unified coordinate system. The integration of 3D information improves vein detection, particularly in low-contrast regions, while also enabling direct and accurate measurements of leaf area, vein length, and VLA. However , this approach also introduces some false positives in vein segmentation due to mesophyll surface variability. Despite these challenges, our high-resolution 3D imaging method shows significant potential for non-invasive phenotyping and trait assessment in complex, unstructured environments.