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The detailed structure information under the forest canopy is important for forestry surveying. As a high-precision environmental sensing and measurement method, terrestrial laser scanning (TLS) is widely used in high-precision forestry surveying. In TLS-based forestry surveys, stem-mapping, which is focused on detecting and extracting trunks, is one of the core data processing tasks and the basis for the subsequent calculation of tree attributes; one of the most basic attributes is the diameter at breast height (DBH). This article explores and improves the methods for stem mapping and DBH estimation from TLS data. Firstly, an improved 3D stem mapping algorithm considering the growth direction in random sample consistency (RANSAC) cylinder fitting is proposed to extract and fit the individual tree point cloud section. It constructs the hierarchical optimum cylinder of the trunk and introduces the growth direction into the establishment of the backbone buffer in the next layer. Experimental results show that it can effectively remove most of the branches and reduce the interference of the branches to the discrimination of trunks and improve the integrity of stem extraction by about 36%. Secondly, a robust least squares ellipse fitting method based on the elliptic hypothesis is proposed for DBH estimation. Experimental results show that the DBH estimation accuracy of the proposed estimation method is improved compared with other methods. The mean root mean squared error (RMSE) of the proposed estimation method is 1.14 cm, compared with other methods with a mean RMSE of 1.70, 2.03, and 2.14 cm. The mean relative accuracy of the proposed estimation method is 95.2%, compared with other methods with a mean relative accuracy of 92.9%, 91.9%, and 90.9%.

To enhance the precision and robustness of the three-frame phase shift technique, a new three-frame random phase-shifting fringe pattern phase demodulation method that combines VU decomposition and ellipse fitting techniques without the need for pre-filtering is proposed. The proposed method first performs VU decomposition on the interferograms to establish two orthogonal components of the fringe pattern. Then, the ellipse fitting method is used to obtain the relevant ellipse coefficients, thereby achieving precise phase demodulation. This method does not require an accurate phase-shifting process, thereby relaxing the stringent requirements on the phase shifter. Compared with traditional algorithms, the proposed method performs better under conditions of non-uniform background intensity and modulation amplitude. Numerical simulation experiments demonstrate that the proposed method maintains good stability across 20 repeated tests. Within the SNR range of 30 to 50 dB, the RMSE of the suggested approach is approximately 0.006 rad. This proves the effectiveness of the algorithm and provides a new approach for the development of three-frame phase-shifting technology.

In this work, we explore the nature of z > 1 galactic bars. Once thought to be highly transient, our results demonstrate otherwise. Our sample consists of nine massive (>1010.5 M⊙) star-forming barred-spiral galaxies at zspec ∼ 1.5. Using rest-frame near-IR (F444W) JWST/NIRCam imaging, we apply ellipse fitting along with 1D and 2D morphological modeling to directly measure bar properties. We find that five galaxies host flat surface brightness profiles (bar Sérsic index < 0.4), indicative of highly evolved, “mature” bars. By contrast, only two galaxies show exponential profiles, characteristic of young bars, and these are also shorter in absolute length than the flat bars. We therefore conclude that a large fraction of bars at this epoch have already matured, thereby indicating the presence of well-settled disks required to facilitate bar formation and sustained evolution well before z ∼ 1.5. To assess the gravitational impact of the bars, we calculate the maximum transverse-to-radial force ratio (Qb). We find that the Qb values are comparable to, or weaker than, those of bars in the local Universe; seven of the nine bars show only a marginal increase in strength with maturity (from exponential to flat bars). Contrarily however, the remaining two bars are flat, but have the lowest Qb values in our sample. We hence propose that the mature bars at z ∼ 1.5 may experience phases of weakening due to rapid gas inflows and/or minor mergers. In conclusion, our work sheds light on the rapidly evolving nature of high-z bars and paves the way for larger statistical studies.

We have examined the stellar structure of 10 nearby, low stellar mass (106–6 × 107 M⊙) dwarf irregular galaxies by fitting ellipses as a function of surface brightness on ultradeep V images. These are compared to far-ultraviolet images as tracers of the star formation. We find that the often asymmetrical distribution of large patches of star formation activity in dwarfs, even out to low disk surface brightness levels, skews the broad-band optical isophotes in these galaxies. We also looked for evidence of the presence of a stellar halo. Possible hints of such are found in several galaxies from irregularities in the ellipses, but a stack of seven of the galaxies shows a pure exponential out to a V surface brightness of 32.3 mag arcsec−2 where the stellar surface density is 0.0013 ± 0.0011 M⊙ pc−2. The extended stellar component, most likely a disk structure, is probably due to internal evolutionary processes rather than external accretion. The UBVI colors of the annuli are consistent with ages of 1–6 Gyr for the far outer stellar disk.

We propose a novel minimal solver for sphere fitting via its 2D central projection, i.e., a special ellipse. The input of the presented algorithm consists of contour points detected in a camera image. General ellipse fitting problems require five contour points. However, taking advantage of the isotropic spherical target, three points are enough to define the tangent cone parameters of the sphere. This yields the sought ellipse parameters. Similarly, the sphere center can be estimated from the cone if the radius is known. These proposed geometric methods are rapid, numerically stable, and easy to implement. Experimental results—on synthetic, photorealistic, and real images—showcase the superiority of the proposed solutions to the state-of-the-art methods. A real-world LiDAR-camera calibration application justifies the utility of the sphere-based approach resulting in an error below a few centimeters.

Galaxy model subtraction removes the smooth light of nearby galaxies so that fainter sources (e.g., stars, star clusters, and background galaxies) can be identified and measured. Traditional approaches (isophotal or parametric fitting) are semiautomated and can be challenging for large datasets. We build a convolutional denoising autoencoder (DAE) for galaxy model subtraction: images are compressed to a latent representation and reconstructed to yield the smooth galaxy, suppressing other objects. The DAE is trained on GALFIT-generated model galaxies injected into real sky backgrounds and tested on real images from the Next Generation Virgo Cluster Survey. To quantify performance, we conduct an injection-recovery experiment on residual images by adding mock globular clusters (GCs) with known fluxes and positions. Our tests confirm a higher recovery rate of mock GCs near galaxy centers for complex morphologies, while matching ellipse fitting for smooth ellipticals. Overall, the DAE achieves subtraction equivalent to isophotal ellipse fitting for regular ellipticals and superior results for galaxies with high ellipticities or spiral features. Photometry of small-scale sources on DAE residuals is consistent with that on ellipse-subtracted residuals. Once trained, the DAE processes an image cutout in ≲0.1 s, enabling fast, fully automatic analysis of large datasets. We make our code available for download and use.

To reduce the great influence on the operation of the transmission lines resulted from the external force damage of the insulator, and to improve the operation and maintenance level of the lines, a composite insulator defect identification method based on random Hough transform ellipse detection is proposed in this paper. This method takes the image of the insulator taken by drone aerial photography as the research object. First, the edge of the insulator is extracted by the Canny operator. Then, an ellipse curve fitting is applied to the extracted edge. Finally, the edge curve of the composite insulator is compared with the fitted elliptic curve, and the defect area is identified. This method cannot only identify the breakage state of the insulator, but also evaluate the degree of damage by comparing the damaged area.

The convergence diameter of shield tunnels is detected by ellipse fitting or local curve fitting to cross-section points. However, the tunnel section, which is extruded by an external force, has an irregular elliptical shape, and the waist of the tunnel is often blocked by accessories, resulting in data loss. This study proposes a convergence diameter and radial dislocation detection method based on block-level fitting. The proposed method solves the accuracy degradation caused by the model error and point cloud incompletion. First, the noise points in the tunnel section point cloud are removed using the least trimmed squares method. Second, the tunnel transverse seam is then located using the image edge detection algorithm. Third, the endpoint of the convergence diameter is determined by making a specific segment the center and shifting the detector from the center to the pinpoint. Finally, the convergence diameter and radial dislocation are detected by the endpoints of the segments. The experimental results showed that the absolute detection accuracy of this method was better than 3 mm, and the repeated detection accuracy was better than 2 mm. This result is consistent with prior total station measurements, which are more suitable for practical engineering applications.

Edge detection is one of the most fundamental and critical operations in image analysis and computer vision. This paper proposes an adaptive edge detection method that combines multi-scale closest neighbor operator with grid partition technique (MSCNOGP). The multi-scale closest neighbor operator can be used to remove both noisy data and small area textures, while the grid partition technique can improve the precision of the edges. By utilizing the concepts of both twin edge pixel and grid divergence, the resulting edges can be further improved. Compared with prevailing traditional methods, the MSCNOGP method achieves both the best precision and almost the best visual effect, where both line segment fitting and ellipse fitting are applied for testing different edge detection methods. The performance on the F-measure score of the MSCNOGP method is much better than those of prevailing traditional methods.

Taking advantage of the gradual change characteristic of the curvature of the conventional conic ellipse, this paper proposes a method of fitting a non-uniform rational B-spline (NURBS) curve with an elliptical arc and, thereafter, performing speed planning and interpolation of the elliptical arc itself. First, the method of elliptical arc fitting is introduced and then proven by simulation with comparative previous linear and arc fittings to obtain better fitting accuracy with fewer segments. Subsequently, the tangent vector of any point of an ellipse is used to complete the speed planning and interpolation of that ellipse. In terms of speed planning, the maximum acceleration of any point in the elliptical arc can be obtained by using a tangent vector, and the time speed curve in this work is completed based on this phenomenon. In the interpolation stage, the longest axis of the current point is determined by using the tangent vector of any point of the elliptical arc, according to which the pulse is sent, thereby completing the interpolation operation via this iterative cycle. This method unifies the processing model of the interpolation algorithm, the simplicity and efficiency of which is verified by subsequent simulation data. This method can also be universally applied to processing most other types of curve.