Reliable Point Research Articles

Reliable measures of rest-activity rhythm fragmentation: how many days are needed?

BackgroundA more fragmented, less stable rest-activity rhythm (RAR) is emerging as a risk factor for health. Accelerometer devices are increasingly used to measure RAR fragmentation using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probabilities (TP), self-similarity parameter (α), and activity balance index (ABI). These metrics were proposed in the context of long period of wear but, in real life, non-wear might introduce measurement bias. This study aims to determine the minimum number of valid days to obtain reliable fragmentation metrics.MethodsWrist-worn accelerometer data were drawn from the Whitehall accelerometer sub-study (age: 60 to 83 years) to simulate different non-wear patterns. Pseudo-simulated data with different numbers of valid days (one to seven), defined as < 1/3 of non-wear during both day and night periods, and with omission or imputation of non-wear periods were compared against complete data using intraclass correlation coefficient (ICC) and mean absolute percent error (MAPE).ResultsFive days with valid data (97.8% of participants) and omission of non-wear periods allowed an ICC ≥ 0.75 and MAPE ≤ 15%, acceptable cut points for reliability, for IS and ABI; this number was lower for TPs (two-three days), α and IV (four days). Overall, imputation of data did not provide better estimates. Findings were consistent across age and sex groups.ConclusionsThe number of days of wrist accelerometer data with at least 2/3 of wear time for both day and night periods varies from two (TPs) to five (IS, ABI) days for reliable RAR measures among older adults.

Weakly supervised 3D point cloud semantic segmentation for architectural heritage using teacher-guided consistency and contrast learning

Point cloud semantic segmentation is significant for managing and protecting architectural heritage. Currently, fully supervised methods require a large amount of annotated data, while weakly supervised methods are difficult to transfer directly to architectural heritage. This paper proposes an end-to-end teacher-guided consistency and contrastive learning weakly supervised (TCCWS) framework for architectural heritage point cloud semantic segmentation, which can fully utilize limited labeled points to train network. Specifically, a teacher-student framework is designed to generate pseudo labels and a pseudo label dividing module is proposed to distinguish reliable and ambiguous point sets. Based on it, a consistency and contrastive learning strategy is designed to fully utilize supervision signals to learn the features of point clouds. The framework is tested on the ArCH dataset and self-collected point cloud, which demonstrates that the proposed method can achieve effective semantic segmentation of architectural heritage using only 0.1 % of annotated points.

Enhanced Biomechanical Properties of the Pectineal Ligament Support Its Reliability for Apical Pelvic Organ Prolapse Repair

Pelvic organ prolapse impacts an increasing number of women in the United States. The standard approach to correcting apical pelvic organ prolapse uses the sacral anterior longitudinal ligament (SALL) to lift the vaginal apex; however, this approach may result in recurrent prolapse. A newer procedure utilizes the pectineal ligament (PL), which may be a more reliable anchor point. This study compares the biomechanical properties of these two ligaments to elucidate which can withstand more stress to provide long-term stability following prolapse. Seventeen formalin-embalmed donors were used (PL: 17 right, 16 left; SALL, 15). The PL was evaluated to better characterize the ligament’s properties within the pelvis using digital calipers and descriptive statistics. Mean values were statistically evaluated using an independent t test (p = 0.05) but no differences in laterality were appreciable. The PL and SALL samples were harvested and evaluated using a mechanical tester to determine their force at failure (N), toughness (Jm−2), and elastic modulus (MPa). The PL had increased values in the mean force at failure and toughness than the SALL when evaluated by each side as well as a combined mean value. These differences were statistically significant (p = 0.05) for toughness as evaluated using an independent t-test (right, p = 0.004; left, p = 0.005; combined, p = 0.002) and force at failure [right, p = 0.001 (independent t-test); left, p = 0.004 and combined, p = 0.005 (Mann–Whitney U test)], indicating that the PL may permit more deformation, but greater resistance to catastrophic failure as compared to the SALL. When evaluating any statistical differences in modulus, the individual and combined values were increased for the PL as compared to the SALL but were not significant (right, p = 0.290; left, p = 0.143; combined, p = 0.110) suggesting a stiffer material that may be more prone to catastrophic failure once a tear has begun. Collectively, these inherent biomechanical properties of the pectineal ligament indicate the ligament may be a more reliable anchor point for pelvic organ prolapse repair than the SALL.

Enhancing PV system grid stability through reliable flexible power point tracking under partial shading

Enhancing PV system grid stability through reliable flexible power point tracking under partial shading

Intensive study, tuning and modification of reactive routing approach to improve flat FANET performance in data collection scenario.

The Flying Ad-hoc Network (FANET) can be defined as the Ad-hoc network that connects unmanned aerial vehicles flying in the space with each other and with a ground base station. However, the 3D movement of these drones with higher speeds results in a network of highly dynamic topology and intermittent connections, making the standard Ad Hoc routing protocols are not suitable for FANET. The approaches followed to address this issue include designing from scratch a routing protocol specific to FANET or modifying the existing protocols. From the view point of reliability, accuracy, and time, it is preferable to base the work on a protocol standard. But before amending the standard, tuning its performance and applying it under suitable conditions may be satisfactory for the new use. Therefore, this work considers flat FANET of fully mission-controlled drones and performs an extensive parametric simulation study to determine the best conditions and parameters' values for applying the popular Ad Hoc On-demand Distance Vector (AODV) to it. After deducing the recommended operating environment (FAODVN-OE), some examples of amendments were suggested to further improve the performance. It was found that the modified FAODVN-OE achieves high performance compared to the default standard in terms of jitter and delay. It helped reduce jitter and delay by an average of 93.2% and 83.8%, respectively, while exhausting less energy; however the network experiences a 24.5% reduction in packet delivery ratio.

Quantifying Variation in the Physical Size of Footwear Test Impressions

The analysis of forensic footwear evidence often requires the preparation of test impressions created under controlled laboratory conditions. When these test impressions are compared to questioned impressions, (dis)agreement in physical size is an important attribute that must be evaluated and documented. Integral to this comparison is an understanding of the variation that may exist between replicate test impressions, and test impressions created using different methods. The aim of this study was to empirically characterize the variation that exists within and between test impressions prepared using a static benchtop and a dynamic walking method, as well as explore the potential influence of the wearer’s foot size when using the walking method. To examine this variation, twenty-three participants were recruited to prepare test impressions of two different shoe makes and models in four different manufacturer’s sizes. Five replicate benchtop impressions per make/model/size and three replicate walking impressions per participant/make/model/size were created, resulting in approximately 550 test samples, to which an additional 150 quality control copies were blindly added, resulting in almost 700 processed test impressions. Using reproducible and reliable ground control points, the physical size of toe-to-heel length and medial-to-lateral ball of the toe width measurements were collected and compared. For the shoe make/models examined in this study, a systematic bias was observed between benchtop and walking impressions, such that benchtop impressions were almost always longer and narrower than walking impressions, and that within the walking method, physical size differences vary with foot/shoe size mismatch. Of the experimental shoes and groups examined in this study, the variation in toe-to-heel length measurements between benchtop and walking impressions was greatest when the shoe was two sizes smaller than the foot, resulting in a maximum physical size difference of 4.18 mm for a Nike® Downshifter 11 outsole. Similarly, when comparing the variation in toe-to-heel length measurements between walking impressions created using a correctly-fitted shoe versus a shoe that was two sizes smaller than the wearer’s foot, a maximum physical size difference of 3.25 mm was observed. Based on these findings, best practice suggests that footwear analysts document the foot size of the wearer preparing walking test impressions, refrain from using benchtop impressions to form opinions about physical size consistency/differences, and to be cognizant that a large mismatch between shoe/foot size when creating walking impressions can lead to length differences greater than 3.0 mm.

Peer review of the pesticide risk assessment of the active substance pirimicarb.

The conclusions of the European Food Safety Authority (EFSA) following the peer review of the initial risk assessments carried out by the competent authorities of the rapporteur Member State Sweden for the pesticide active substance pirimicarb are reported. The context of the peer review was that required by Commission Implementing Regulation (EU) No 844/2012, as amended by Commission Implementing Regulation (EU) No 2018/1659. The conclusions were reached on the basis of the evaluation of the representative use(s) of pirimicarb as an insecticide on winter and spring wheat and sugar beet via foliar spray application and on ornamental pot plants in permanent greenhouses. The reliable end points, appropriate for use in regulatory risk assessment are presented. Missing information identified as being required by the regulatory framework is listed. Concerns are identified.

Peer review of the pesticide risk assessment of the active substance pyrimethanil.

The conclusions of the European Food Safety Authority (EFSA) following the peer review of the initial risk assessments carried out by the competent authorities of the rapporteur Member State Czech Republic and co-rapporteur Member State Austria for the pesticide active substance pyrimethanil and of confirmatory data following the maximum residue limit (MRL) review under Article 12 of Regulation (EC) No 396/2005 are reported. The context of the peer review was that required by Commission Implementing Regulation (EU) No 844/2012, as amended by Commission Implementing Regulation (EU) No 2018/1659. The conclusions were reached on the basis of the evaluation of the representative uses of pyrimethanil as a fungicide on grapevine and pome fruit (field uses), strawberry and lettuce (field and greenhouse uses). The reliable end points, appropriate for use in regulatory risk assessment are presented. Missing information identified as being required by the regulatory framework is listed. Concerns are identified.

Peer review of the pesticide risk assessment of the active substance penoxsulam

Abstract The conclusions of the European Food Safety Authority (EFSA) following the peer review of the initial risk assessments carried out by the competent authorities of the rapporteur Member State, Italy, and co‐rapporteur Member State, Poland, for the pesticide active substance penoxsulam are reported. The context of the peer review was that required by Commission Implementing Regulation (EU) No 844/2012, as amended by Commission Implementing Regulation (EU) No 2018/1659. The conclusions were reached on the basis of the evaluation of the representative uses of penoxsulam as a herbicide on rice and chicory. The reliable end points, appropriate for use in regulatory risk assessment, are presented. Missing information identified as being required by the regulatory framework is listed. Concerns are reported where identified.

The prognostic utility of the neutrophil to lymphocyte ratio in paediatric brain tumours: a retrospective case control study

Introduction Paediatric brain tumours (PBT) are the most common cause of death among all childhood cancers. The neutrophil to lymphocyte ratio (NLR) has been shown to prognosticate many adult cancers. There is a paucity of literature on the NLR in PBTs. This study aims to study the link between PBTs and the NLR by comparing the preoperative serum NLR in children under 16 with brain tumours with their outcome in terms of grade of brain tumour and overall survival. Methods This is a retrospective case control study. The NLRs were compared between patients with benign or malignant PBTs and patients who were alive or dead. Receiver-operating characteristic (ROC) curve analyses were performed and Youden indexes were calculated to evaluate the predictive potential of the NLR. A cut-off point of NLR > 4 was selected for the calculation of odds ratios. Results A total of 515 patients were included in this study. 53.8% were male. 66.2% had benign PBTs. 81.0% were alive at the time of the study. Patients with malignant PBTs had a higher NLR compared to patients with benign PBTs (p = 0.0066**). There was no difference in the NLR between patients who were dead compared to those who were alive (p = 0.1682 ns). The NLR had a Youden’s index of 0.1567 to predict malignant PBTs and 0.1285 to predict survival. Conclusion A high NLR was associated with an increased odds of having a malignant PBT but a reliable cut-off point was not identified and the underlying mechanisms for this remain unknown. The NLR is a poor diagnostic biomarker due to its poor overall sensitivity and specificity. More research is required to further study the role of immunity in PBTs.

Challenges and Opportunities of Sentinel-1 InSAR for Transport Infrastructure Monitoring

Monitoring displacement at transport infrastructure using Sentinel‑1 Interferometric Synthetic Aperture Radar (InSAR) faces challenges due to the sensor’s medium spatial resolution, which limits the pixel coverage over the infrastructure. Therefore, carefully selecting coherent pixels is crucial to achieve a high density of reliable measurement points and to minimize noisy observations. This study evaluates the effectiveness of various pixel selection methods for displacement monitoring within transport infrastructures. We employ a two-step InSAR time series processing approach. First, high-quality first-order pixels are selected using temporal phase coherence (TPC) to estimate and correct atmospheric contributions. Then, a combination of different pixel selection methods is applied to identify coherent second-order pixels for displacement analysis. These methods include amplitude dispersion index (ADI), TPC, phase linking coherence (PLC), and top eigenvalue percentage (TEP), targeting both point-like scatterer (PS) and distributed scatterer (DS) pixels. Experiments are conducted in two case studies: one in Germany, characterized by dense vegetation, and one in Spain, with sparse vegetation. In Germany, the density of measurement points was approximately 30 points/km², with the longest segment of the infrastructure without any coherent pixels being 2.8 km. In Spain, the density of measurement points exceeded 500 points/km², with the longest section without coherent pixels being 700 meters. The results indicate that despite the challenges posed by medium-resolution data, the sensor is capable of providing adequate measurement points when suitable pixel selection methods are employed. However, careful consideration is necessary to exclude noisy pixels from the analysis. The findings highlight the importance of choosing a proper method tailored to infrastructure characteristics. Specifically, combining TPC and PLC methods offers a complementary set of pixels suitable for displacement measurements, whereas ADI and TEP are less effective in this context. This study demonstrates the potential of Sentinel‑1 InSAR for capturing both regional-scale and localized displacements at transport infrastructure.

Peer review of the pesticide risk assessment of the active substance flufenacet.

The conclusions of the European Food Safety Authority (EFSA) following the peer review of the initial risk assessments carried out by the competent authorities of the rapporteur Member State Poland and co-rapporteur Member State France for the pesticide active substance flufenacet are reported. In addition, the assessment of the confirmatory data following the Article 12 maximum residue limit (MRL) review of Regulation (EC) No 396/2005 is also reported. The context of the peer review was that required by Commission Implementing Regulation (EU) No 844/2012. The conclusions were reached on the basis of the evaluation of the representative use of flufenacet as a herbicide on winter cereals. Confirmatory data following the Article 12 MRL review were assessed. The reliable end points, appropriate for use in regulatory risk assessment and the assessment of confirmatory data following the Article 12 MRL review, are presented. Missing information identified as being required by the regulatory framework is listed. Concerns are reported where identified.

Estimation of Stress–Strength Reliability for Power Transformed Perks Distribution with Applications

The power transformation of the Perks distribution, its survival, and hazard functions are computed. The shapes of hazard function are obtained analytically which shows that this model has increasing and decreasing hazard rates. In the stress–strength reliability estimation, point and interval estimates are computed using maximum likelihood and asymptotic confidence interval methods, respectively. The performance of the estimates is evaluated through the Monte Carlo simulation and the applications of the proposed distribution to three real datasets have been demonstrated.

Automatic personal identification using a single CT image.

Computer vision (CV) mimics human vision, enabling computers to automatically compare radiological images from recent examinations with a large image database for unique identification, crucial in emergency scenarios involving unknown patients or deceased individuals. This study aims to extend a CV-based personal identification method from orthopantomograms (OPGs) to computed tomography (CT) examinations using single CT slices. The study analyzed 819 cranial computed tomography (CCT) examinations from 722 individuals, focusing on single CT slices from six anatomical regions to explore their potential for CV-based personal identification in 69 procedures. CV automatically identifies and describes interesting features in images, which can be recognized in a reference image and then designated as matching points. In this study, the number of matching points was used as an indicator for identification. Across six different regions, identification rates ranged from 41/69 (59%) to 69/69 (100%) across over 700 possible identities. Comparison of images from the same individual achieved higher matching points, averaging 6.32 ± 0.52% (100% represents the maximum possible matching points), while images of different individuals averaged 0.94 ± 0.15%. Reliable matching points are found in the teeth, maxilla, cervical spine, skull bones, and paranasal sinuses, with the maxillary sinuses and ethmoidal cells being particularly suitable for identification due to their abundant matching points. Unambiguous identification of individuals based on a single CT slice is achievable, with maxillary sinus CT slices showing the highest identification rates. However, metal artifacts, especially from dental prosthetics, and various head positions can hinder identification. Radiology possesses a multitude of reference images for a CV database, facilitating automated CV-based personal identification in emergency examinations or cases involving unknown deceased individuals. This enhances patient care and communication with relatives by granting access to medical history. Unknown individuals in radiology or forensics pose challenges, addressed through automatic CV-based identification methods. A single CT slice highlighting the maxillary sinuses is particularly effective for personal identification. Radiology plays a pivotal role in automated personal identification by leveraging its extensive image database.

Highly robust thermal infrared and visible image registration with canny and phase congruence detection

When a dual-optical vehicle-mounted camera is photographed, visible and thermal infrared (VI-T) images cannot be registered, and realising fine matching of the images to solve for the optimal affine parameters is thus key to this research. Visible and thermal image matching is of great interest owing to the presence of challenging scale transformations, nonlinear radial aberrations, and robustness under illumination conditions. Thus, this paper presents a novel algorithm, namely, Highly Robust Thermal Infrared and Visible Image Registration with Canny and Phase Congruence Detection (HRCP). Firstly, the image is pre-processed, and feature point detection is performed by combining adaptive thresholding GW-Canny edge detection and phase coherence (PC), which increases the edge information. Secondly, SURF and FAST feature detection at the maximum distance of PC maps can obtain stable and reliable feature points, which are robust to scale invariance and rotation invariance. Finally, the optimal affine parameter is solved using the least square method with several iterations. Compared to existing matching methods, we find that VI-T image matching is particularly sensitive to both lighting factors and scale-transformed nonlinear radial distortion and that HRCP is robust in performing matching. For the randomly selected dataset, the average image matching time is reduced by 3.265 s, the number of correct image matches increases by 44 pairs on average, the root mean square error improves to 1.830, and the average error improves to 2.815. The proposed method not only improves the inaccuracy of radiation-insensitive feature transform matching in both low and high light, but also achieves a higher accuracy and an increase in the number of feature matching points, which facilitates robust VI-T image registration.

TSG-Seg: Temporal-selective guidance for semi-supervised semantic segmentation of 3D LiDAR point clouds

LiDAR-based semantic scene understanding holds a pivotal role in various applications, including remote sensing and autonomous driving. However, the majority of LiDAR segmentation models rely on extensive and densely annotated training datasets, which is extremely laborious to annotate and hinder the widespread adoption of LiDAR systems. Semi-supervised learning (SSL) offers a promising solution by leveraging only a small amount of labeled data and a larger set of unlabeled data, aiming to train robust models with desired accuracy comparable to fully supervised learning. A typical pipeline of SSL involves the initial use of labeled data to train segmentation models, followed by the utilization of predictions generated from unlabeled data, which are used as pseudo-ground truths for model retraining. However, the scarcity of labeled data limits the capture of comprehensive representations, leading to the constraints of these pseudo-ground truths in reliability. We observed that objects captured by LiDAR sensors from varying perspectives showcase diverse data characteristics due to occlusions and distance variation, and LiDAR segmentation models trained with limited labels prove susceptible to these viewpoint disparities, resulting in inaccurately predicted pseudo-ground truths across viewpoints and the accumulation of retraining errors. To address this problem, we introduce the Temporal-Selective Guided Learning (TSG-Seg) framework. TSG-Seg explores temporal cues inherent in LiDAR frames to bridge the cross-viewpoint representations, fostering consistent and robust segmentation predictions across differing viewpoints. Specifically, we first establish point-wise correspondences across LiDAR frames with different time stamps through point registration. Subsequently, reliable point predictions are selected and propagated to points from adjacent views to the current view, serving as strong and refined supervision signals for subsequent model re-training to achieve better segmentation. We conducted extensive experiments on various SSL labeling setups across multiple public datasets, including SemanticKITTI and SemanticPOSS, to evaluate the effectiveness of TSG-Seg. Our results demonstrate its competitive performance and robustness in diverse scenarios, from data-limited to data-abundant settings. Notably, TSG-Seg achieves a mIoU of 48.6% using only 5% of and 62.3% with 40% of labeled data in the sequential split on SemanticKITTI. This consistently outperforms state-of-the-art segmentation methods, including GPC and LaserMix. These findings underscore TSG-Seg’s superior capability and potential for real-world applications. The project can be found at https://tsgseg.github.io.

Peer review of the pesticide risk assessment of the active substance triclopyr (variant triclopyr-butotyl).

The conclusions of the European Food Safety Authority (EFSA) following the peer review of the initial risk assessments carried out by the competent authorities of the rapporteur Member State Poland and co-rapporteur Member State Hungary for the pesticide active substance triclopyr (variant triclopyr-butotyl) and the assessment of applications for maximum residue levels (MRLs) are reported. The context of the peer review was that required by Commission Implementing Regulation (EU) No 844/2012, as amended by Commission Implementing Regulation (EU) No 2018/1659. The conclusions were reached on the basis of the evaluation of the representative uses of triclopyr (variant triclopyr-butotyl) as a herbicide on established pasture and non-recreational amenity grassland (field use). MRLs were assessed in rice. The reliable end points, appropriate for use in regulatory risk assessment and the proposed MRLs, are presented. Missing information identified as being required by the regulatory framework is listed. Concerns are reported where identified.

Prediction of Flash Point of Materials Using Bayesian Kernel Machine Regression Based on Gaussian Processes With LASSO‐Like Spike‐and‐Slab Hyperprior

ABSTRACTThe determination of flash points is a critical aspect of chemical safety, essential for assessing explosion hazards and fire risks associated with flammable solutions. With the advent of new chemical blends and the increasing complexity of chemical waste management, the need for accurate and reliable flash point prediction methods has become more pronounced. This study introduces a novel predictive approach using Bayesian kernel machine regression (BKMR) with Gaussian process priors, designed to meet the growing demand for precise flash point estimation in the context of chemical safety. The BKMR model, underpinned by Bayesian statistics, offers a comprehensive framework that not only quantifies prediction uncertainty but also enhances interpretability amidst experimental data variability. Our comparative analysis reveals that BKMR surpasses traditional predictive models, including support vector machines, kernel ridge regression, and Gaussian process regression, in terms of accuracy and reliability across multiple metrics. By elucidating the intricate interactions between molecular features and flash point properties, the BKMR model provides profound insights into the chemical dynamics that influence flash point determinations. This study signifies a methodological leap in flash point prediction, offering a valuable tool for chemical safety analysis and contributing to the development of safer chemical handling and storage practices.

LOGICAL-PROBABLIC MODELING OF FAILURES OF GEODESIC NETWORKS

The credibility and reliability of the results of geodetic and cadastral works depends mainly on the accuracy of the instruments, the qualification of the observer, his professionalism and the reliability of the points of the geodetic network (GN). As a rule, in most cases, there is a well-founded choice of geodetic tools suitable for accuracy and the involvement of a highly qualified geodetic engineer to perform certain types of geodetic work. However, certain questions may arise regarding the determination of starting points for the creation of a reliable geodetic survey justification. The issue of selecting reliable geodetic points for performing engineering and geodetic works based on the application of reliability assessment methods is an urgent scientific problem today. The purpose of the work is to establish the optimal reliability assessment method based on the analysis of existing ones. Adapt this method to solve the problem of assessing the reliability of geodetic networks as one of the most important parameters characterizing its condition. Assess the reliability of the Dnipro geodetic network by constructing a fault tree. Calculate the dynamics of the intensity of GN failures during the 100-year period of its existence. Calculate the appropriate periodicity of surveys (monitoring) of GN depending on the intensity of failures of elements (geodetic points). Methodology. Analysis of international and national standards for reliability assessment, Standards of Ukraine, where the methods of system reliability assessment are given. Review of methods for assessing GN reliability. The deductive method with the construction of a geodetic network failure tree has been applied. This method is based on a logic-probabilistic model of cause-and-effect relationships of system failures with failures of its elements and other events. Scientific novelty. The optimal method of assessing the reliability of GN has been established. A GN failure tree has been built in the TopEvent FTA software tool. The reliability of the geodetic network has been evaluated, the intensity of failures at various stages of its operation has been calculated. Mathematical expressions of the failure functions of the geodetic network have been described by applying Boolean functions. Practical value. International and national regulatory documents and Standards of Ukraine of reliability assessment have been analyzed. In Standarts the methods of system reliability assessment have been given. The performed assessment of the reliability of the state of the geodetic network of the city of Dnipro helps to choose stable geodetic points for the creation of local geodetic networks and survey justification. Reasonable periodicity of monitoring for the survey of geodetic points has been substantiated. The use of reliable points of geodetic networks will allow obtaining reliable observation data, which will significantly increase the quality of engineering and geodetic works. Results. The functioning of the geodetic network of the city of Dnipro on the constructed sequential tree of failures has been considered. Boolean functions to describe the mathematical expressions of the failure functions of the geodetic network, which includes 5 and 10 elements have been used.

Weak-Texture Seafloor and Land Image Matching Using Homography-Based Motion Statistics with Epipolar Geometry

The matching of remote sensing images is a critical and necessary procedure that directly impacts the correctness and accuracy of underwater topography, change detection, digital elevation model (DEM) generation, and object detection. The texture of images becomes weaker with increasing water depth, and this results in matching-extraction failure. To address this issue, a novel method, homography-based motion statistics with an epipolar constraint (HMSEC), is proposed to improve the number, reliability, and robustness of matching points for weak-textured seafloor images. In the matching process of HMSEC, a large number of reliable matching points can be identified from the preliminary matching points based on the motion smoothness assumption and motion statistics. Homography and epipolar geometry are also used to estimate the scale and rotation influences of each matching point in image pairs. The results show that the matching-point numbers for the seafloor and land regions can be significantly improved. In this study, we evaluated this method for the areas of Zhaoshu Island, Ganquan Island, and Lingyang Reef and compared the results to those of the grid-based motion statistics (GMS) method. The increment of matching points reached 2672, 2767, and 1346, respectively. In addition, the seafloor matching points had a wider distribution and reached greater water depths of −11.66, −14.06, and −9.61 m. These results indicate that the proposed method could significantly improve the number and reliability of matching points for seafloor images.