Roughness measurement of leaf surface based on shape from focus

Zhang, Zeqing; Liu, Fei; Zhou, Zhenjiang; He, Yong; Fang, Hui

doi:10.1186/s13007-021-00773-y

Cited by 11 publications

(4 citation statements)

References 28 publications

(38 reference statements)

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“…The focus measure (FM) function is used to extract depth information from the multi-focused image sequence. The 3D morphology of the tested sample surface is reconstructed according to the height information [ 35 , 36 ]. The schematic of the 3D reconstruction based on the SFF algorithm using the ETL is shown in Figure 7 .…”

Section: Principle Of the Colorful 3d Reconstructionmentioning

confidence: 99%

Colorful 3D Reconstruction and an Extended Depth of Field for a Monocular Biological Microscope Using an Electrically Tunable Lens

Cheng,

Liu,

et al. 2024

Biomimetics

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This paper presents a monocular biological microscope with colorful 3D reconstruction and an extended depth of field using an electrically tunable lens. It is based on a 4f optical system with an electrically tunable lens at the confocal plane. Rapid and extensive depth scanning while maintaining consistent magnification without mechanical movement is achieved. We propose an improved Laplacian operator that considers pixels in diagonal directions to provide enhanced fusion effects and obtain more details of the object. Accurate 3D reconstruction is achieved using the shape-from-focus method by tuning the focal power of the electrically tunable lens. We validate the proposed method by performing experiments on biological samples. The 3D reconstructed images obtained from the biological samples match the actual shrimp larvae and bee antenna samples. Two standard gauge blocks are used to evaluate the 3D reconstruction performance of the proposed method. The experimental results show that the extended depth of fields are 120 µm, 240 µm, and 1440 µm for shrimp larvae, bee tentacle samples, and gauge blocks, respectively. The maximum absolute errors are −39.9 μm and −30.6 μm for the first and second gauge blocks, which indicates 3D reconstruction deviations are 0.78% and 1.52%, respectively. Since the procedure does not require any custom hardware, it can be used to transform a biological microscope into one that effectively extends the depth of field and achieves highly accurate 3D reconstruction results, as long as the requirements are met. Such a microscope presents a broad range of applications, such as biological detection and microbiological diagnosis, where colorful 3D reconstruction and an extended depth of field are critical.

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Section: Principle Of the Colorful 3d Reconstructionmentioning

confidence: 99%

Colorful 3D Reconstruction and an Extended Depth of Field for a Monocular Biological Microscope Using an Electrically Tunable Lens

Cheng,

Liu,

et al. 2024

Biomimetics

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show abstract

“…Second, the link between weed leaf properties and adjuvant selection is normally ignored during glyphosate application. Third, most of the current studies employ scanning electron microscopy (SEM) to investigate the surface morphology, but the leaf requires to be dehydrated and operated under high vacuum, which cannot be guaranteed artefact-free. − Additional tools are needed to better characterize leaf surfaces and that the proposed technique provides a better understanding of how herbicides penetrate foliage. It may be concluded that an improved method for leaf surface characterization could provide insights into evolved glyphosate resistance and guiding adjuvant selection to reduce formulation toxicity.…”

Section: Introductionmentioning

confidence: 99%

Improved Method to Characterize Leaf Surfaces, Guide Adjuvant Selection, and Improve Glyphosate Efficacy

Zhang

Wang

et al. 2023

J. Agric. Food Chem.

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Glyphosate, one of the most widely used herbicides, plays an important role in controlling weeds and ensuring crop production. While using glyphosate, adjuvants are commonly added to improve its deposition on weeds and control efficacy. However, changes in weed leaf surface characteristics may reduce glyphosate penetration and contribute to evolved glyphosate resistance. Therefore, it is significant to introduce an improved method for regularizing leaf surface characterization and guide adjuvant selection to improve glyphosate efficacy. In this work, surface characteristics of typical weed leaves have been systematically investigated by 3D surface analysis and scanning electron microscopy, finally quantified by apparent surface free energy (ASFE) due to its comprehensive and quantitative evaluation of leaf surfaces. Moreover, the relationship between the weed leaf surface characteristics and the retention of glyphosate on weeds was established, further related to the control efficacy against weeds. To maximize the utilization rate of glyphosate, the types and concentrations of adjuvants should be regulated according to the ASFE of weeds. Our findings not only regularize the surface properties of weed leaves but also reveal their influencing mechanism on the deposition and biological activity of glyphosate, which provide effective guidance for the use of glyphosate.

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“…Hou et al [26] proposed an improved fast-focusing shape method for 3D measurement of key features of fuel nozzles. Zhang et al [27] proposed a focal shape-based method. The algorithm is used to process a given spatially variable blurred image to obtain the surface roughness of plant leaves.…”

Section: Introductionmentioning

confidence: 99%

An image fusion-based method for recovering the 3D shape of roll surface defects

Xu,

Lou

et al. 2023

Meas. Sci. Technol.

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Most of the existing studies on roll surface defects focus on qualitative detection and lack of quantitative analysis, while the commonly used methods for detecting the three-dimensional shape of small objects such as defects are stylus method, laser scanning method and structured light scanning method, but these methods are difficult to accurately measure the complex defect variations on the roll surface. In this paper, we propose a method for recovering the 3D shape of roll surface defects based on image fusion. The traditional 3D reconstruction problem is transformed into a 2D image fusion problem using a focusing method. The non-subsampled shear wave transform (NSST) is used as the base algorithm for image fusion, combined with an enhanced fusion strategy called Mm-PCNN to obtain a fully focused image. The method achieves 3D shape recovery of defects by modelling the relationship between the defect depth, the fully focused image, and the original image. To evaluate the performance of the method, experiments were carried out using data involving craters and scratches on the roll surface. The experimental results show that the proposed method effectively integrates detailed information and achieves a reconstruction error control of less than 4%, thus ensuring higher accuracy and improved noise immunity.

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Roughness measurement of leaf surface based on shape from focus

Cited by 11 publications

References 28 publications

Colorful 3D Reconstruction and an Extended Depth of Field for a Monocular Biological Microscope Using an Electrically Tunable Lens

Colorful 3D Reconstruction and an Extended Depth of Field for a Monocular Biological Microscope Using an Electrically Tunable Lens

Improved Method to Characterize Leaf Surfaces, Guide Adjuvant Selection, and Improve Glyphosate Efficacy

An image fusion-based method for recovering the 3D shape of roll surface defects

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