Photogrammetry Techniques Research Articles

Application of Three-Dimensional Digital Photogrammetry to Quantify the Surface Roughness of Milk Powder.

The surface appearance of milk powders is a crucial quality property since the roughness of the milk powder determines its functional properties, and especially the purchaser perception of the milk powder. Unfortunately, powder produced from similar spray dryers, or even the same dryer but in different seasons, produces powder with a wide variety of surface roughness. To date, professional panelists are used to quantify this subtle visual metric, which is time-consuming and subjective. Consequently, developing a fast, robust, and repeatable surface appearance classification method is essential. This study proposes a three-dimensional digital photogrammetry technique for quantifying the surface roughness of milk powders. A contour slice analysis and frequency analysis of the deviations were performed on the three-dimensional models to classify the surface roughness of milk powder samples. The result shows that the contours for smooth-surface samples are more circular than those for rough-surface samples, and the smooth-surface samples had a low standard deviation; thus, milk powder samples with the smoother surface have lower Q (the energy of the signal) values. Lastly, the performance of the nonlinear support vector machine (SVM) model demonstrated that the technique proposed in this study is a practicable alternative technique for classifying the surface roughness of milk powders.

3D Discrete Fracture Network Modelling from UAV Imagery Coupled with Tracer Tests to Assess Fracture Conductivity in an Unstable Rock Slope: Implications for Rockfall Phenomena

The stability of a rock slope is strongly influenced by the pattern of groundwater flow through the fracture system, which may lead to an increase in the water pressure in partly open joints and the consequent decrease in the rock wall strength. The comprehension of the fracture pattern is a challenging but vital aspect in engineering geology since the fractures’ spatial distribution, connectivity, and aperture guide both the water movement and flow quantity within the rock volume. In the literature, the most accepted methods to hydraulically characterise fractured rocks in situ are the single borehole packer test, the high-resolution flow meters for fractures, and the artificial tracer tests performed in boreholes. However, due to the high cost a borehole requires and the general absence of wells along coastal cliffs, these methods may not be appropriate in rockfall-prone areas. In this study, an unsaturated rocky cliff, strongly affected by rockfalls, was investigated by combining kinematic analysis, Discrete Fracture Network (DFN) modelling, and artificial tracer tests. The DFN model and potential rock block failure mechanisms were derived from high-resolution 3D virtual outcrop models via the Structure from Motion (SfM) photogrammetry technique. An artificial tracer was injected using a double ring infiltrometer atop the recharge zone of the slope to determine the infiltration rate and validate the DFN results. The DFN and tracer test methods are frequently used at different spatial scales and for different disciplines. However, the integration of digital photogrammetry, DFN, and tracer tests may represent a new step in rockfall and landslide studies. This approach made possible the identification of groundwater flow patterns within the fracture system and revealed about a 10-day tracer transit time from the injection area and the monitored slope, with similar conductivity values gathered from both the DFN and tracer test. Planar and wedge failures with volumes ranging from 0.1 and 1 m3 are the most probable failure mechanisms in the areas. The results were consistent with the delay between the intense rainfall and the slope failures previously documented in the study area and with their mechanisms.

UAV Photogrammetry-Based Apple Orchard Blossom Density Estimation and Mapping

Thinning is an important routine for apple growers to manage crop load and improve fruit quality, which can be accomplished through manual, chemical, or mechanical manipulation of flowers and fruitlets. Traditionally, blossom thinning relies on human experts’ visual evaluation of the flower load, a leading indicator of crop load, which can be imprecise and prone to errors. This study aimed to develop an apple blossom density mapping algorithm utilizing point clouds reconstructed through unmanned aerial vehicle (UAV)-based red-green-blue (RGB) imagery and photogrammetry. The algorithm was based on grid average downsampling and white color thresholding, and it was able to generate top-view blossom density maps of user-defined tree height regions. A preliminary field experiment was carried out to evaluate the algorithm’s accuracy using manual blossom counts of apple tree row sections as ground truths, and a coefficient of determination (R2) of 0.85, a root mean square error (RMSE) of 1307, and a normalized RMSE (NRMSE) of 9.02% were achieved. The algorithm was utilized to monitor the blooming of the apple tree rows and was demonstrated to effectively show blossom density variations between different tree rows and dates. The study results suggested the potential of UAVs as a convenient tool to assist precise blossom thinning in apple orchards, while future research should further investigate the reliability of photogrammetry techniques under different image qualities and flight settings as well as the influence of blossom distribution on algorithm accuracy.

THE APPLICATION OF SMARTPHONE BASED STRUCTURE FROM MOTION (SFM) PHOTOGRAMMETRY IN GROUND VOLUME MEASUREMENT

Abstract. The purpose of this research study is to assess the potential using smartphone camera captured images for 3D model reconstruction by using Structure from Motion (SFM) photogrammetry technique, specifically in term of volumetric measurement. In past, the volumetric measurement of surface or object is by using Imaging Station or by professional Terrestrial Laser Scanner (TLS), however such approach is expensive in labour fees and instruments fee respectively. A cheaper alternative is necessary for researcher and industrial to construct 3D model with greater cost efficiency. The improvement of photography and computer vision has introduced the technique of SFM photogrammetry, an alternative in 3D model reconstruction other than TLS. Non-metric camera sensor mounted inside budget smartphone are used to capture images of stockpile and processed by Agisoft Metashape Professional (AMP) software to construct a 3D model. The volumetric measurement is executed and compare with the benchmark which is the model constructed from TLS. Statistics and tables are used to indicate the accuracy of Smartphone based SFM photogrammetry in intuitive manner. The result shows that the volumetric measurement by using smartphone SFM method has significant difference when compared with the benchmark, TLS solution.

Expeditious Low-Cost SfM Photogrammetry and a TLS Survey for the Structural Analysis of Illasi Castle (Italy)

The structural analysis of degraded historical buildings requires an adequate 3D model of the object. Structure from motion (SfM) photogrammetry and laser scanning geomatics techniques can satisfy this request by providing geometrically affordable data. The accuracy and resolution depend on the instruments and procedures used to extract the 3D models. This work focused on a 3D survey of Illasi Castle, a strongly degraded historical building located in northern Italy, aimed at structural analysis in the prevision of a static recovery. A low-cost drone, a single-lens reflex (SLR) camera, and a smartphone were used in the survey. From each acquired dataset, using the integration between the images acquired by the drone and the SLR camera, a 3D model of the building was extracted by means of the SfM technique. The data were compared with high-precision and high-resolution terrestrial laser scanning (TLS) acquisitions to evaluate the accuracy and performance of the fast and low-cost SfM approach. The results showed a standard deviation value for the point cloud comparisons in the order of 2–3 cm for the best solution (integrating drone and SLR images) and 4–7 cm using smartphone images. Finally, the integration of the best SfM model of the external walls and the TLS model of the internal portion of the building was used in finite element (FE) analysis to provide a safety assessment of the structure.

A complex scene pavement crack semantic segmentation method based on dual-stream framework

ABSTRACT Pavement crack detection in complex scenes presents a significant challenge in achieving precise pixel-level accuracy due to the presence of intricate backgrounds, such as water stains, shadows, and repair grouting, which closely resemble cracks in terms of morphology and colour. Consequently, existing approaches often struggle to differentiate these elements, resulting in misclassification and decreased accuracy in corresponding areas. This paper proposes a novel approach, called the Dual-Stream U-Network (DSU-Net), specifically designed for complex scene crack detection. The DSU-Net model employs a dual-stream framework, enabling improved focus on challenging regions and effectively addressing the issue of low recognition accuracy. To construct a comprehensive dataset, photogrammetry techniques are employed to acquire images of cracks, resulting in a dataset comprising 5000 images. Experimental evaluations demonstrate that the trained DSU-Net model achieves a mean F1 score of 74.17% on a test set, surpassing the performance of the state-of-the-art methods which achieved a score of 68.09%. These findings validate the effectiveness of the proposed algorithm in accurately distinguishing water stains, shadows, repair grouting, and cracks. Additionally, the algorithm successfully performs fine-grained extraction of cracks. The promising results obtained in this study indicate the potential practical applicability of the proposed approach in engineering scenarios.

Development of a Dundee Ground Truth imaging protocol for recording indoor crime scenes to facilitate virtual reality reconstruction

Early and accurate visualisation of a crime scene is highly desirable such that a rapid, agile, and informed decision-making process can be undertaken by an investigative team. We present a new standard operating procedure for imaging an indoor scene using DSLR cameras conventionally used by crime scene investigators and examiners. The standard operating procedure (SOP) enables the systematic photography of indoor spaces in such a way that the Structure from Motion (SfM) photogrammetry technique can be implemented, allowing the scene to be recreated in Virtual Reality (VR). To demonstrate the method’s validity, we compare two VR-rendered representations of an example scene using (a) photographs taken by an experienced crime scene examiner using a conventional photographic method and (b) photographs taken by a novice photographer following the developed SOP.

A morphological analysis of historic buildings entries using affordable photogrammetry techniques: Old Tripoli, Lebanon

This article documents and compares selected arched and vaulted entrances of historic buildings in Old Tripoli, Lebanon. The aim is to capture the entrances and their immediate context using low-cost photogrammetry to contribute to the safeguarding process of these endangered monuments. The possibilities of recording the micro as well as macro elements of entry spaces for specific typologies, such as schools, khans, residences and places of worship, are explored in the context of a city under the threat of armed conflict, neglect and environmental risks. Micro-scale analysis focuses on forms such as shape, height, and street width, regardless of the building entry's function. Macroscale analysis considers a typical barrel-vaulted tunnel entry to a historic, residential sector of the city where a 3D photogrammetry model demonstrates the form and function of this network of spaces. The research methodology is divided into two processes: the first is a photographic survey of the entrances using a mobile phone camera, followed by the use of both free and educational licensed photogrammetry software to align and develop the captured images into 3D digital models. The second process is conducting interviews with selected stakeholders, such as historians and building custodians to elicit their stories compared to our understanding of the digitally captured 3D buildings and the wider historic city of Tripoli. We argue that affordable photogrammetry methods are necessary and effective. Acknowledging the limitations of these methods, this article argues that the outputs of the implemented methods not only contribute to the identification of the significance of these monuments, but also provide a valuable set of information to assist in the different processes of safeguarding these endangered assets.

Quantifying and spatializing building material stock and renovation flow for circular economy

The linear system of take, make, and waste, has led to deleterious environmental impacts and material use; circular economy strategies may offer benefits. Since the building sector is a major consumer of materials and contributes to many environmental impacts, it is a prime sector to be examined for the implementation of circular economy strategies. Understanding where and what materials are available due to renovation and demolition/deconstruction is lacking in the U.S. Thus, implementation of circular economy strategies like reuse in buildings will be incremental at best. Material stock and flow analysis can be used to understand baselines via accumulated materials and the material flow of buildings. In this study, we developed a bottom-up model using aspects of our previously developed urban building energy model to analyze the accumulated and renovation flow of specific materials in commercial buildings. We focused on renovation as this area was identified as a gap in the literature. The photogrammetry and image processing techniques in this paper provided the opportunity of using actual physical attributes of buildings instead of assumptions, which improved the accuracy of the bottom-up model. The results showed that concrete (37%), brick (30%), and minerals (17%) comprised most of the accumulated materials. Also, there was notable differences in the distribution of materials in different components. Brick had the highest mass in exterior walls; whereas, the largest mass-based quantities in roofs and floors were insulation and minerals, respectively. Brick followed by minerals and concrete had the largest share of renovation flow during 2020 and 2030. These outcomes aid policy makers and businesses in decision-making regarding the availability of secondary resources from buildings.

Rockfall source areas identification at local scale by integrating discontinuity-based threshold slope angle and rockfall trajectory analyses

Rockfall source areas identification of high steep fractured rock slope is a challenging task for hazard mitigation. Considering this difficulty, a new method integrating discontinuity-based threshold slope angle and rockfall trajectory analyses is introduced in this study and applied to a railway bridge in China. First, abundant discontinuity data are collected by means of the modern unmanned aerial vehicle (UAV) digital photogrammetry technique. Then, a threshold slope angle used to delineate rockfall-prone areas is comprehensively determined by probabilistic kinematic and block theory analyses. Next, physically based rockfall trajectory simulation with consideration of mean block size is used to distinguish the hazard level of each release point. Finally, rockfall sources causing moderate and high risks to the train tunnel entrance at the base of high steep fractured rock slope are determined using a semiquantitative risk matrix approach. The final rockfall source map can provide a quantitative reference for hazard mitigation. At the end of this paper, some issues associated with the proposed approach are discussed, such as parameter importance analysis of threshold slope angle, comparison between the two probabilistic approaches and uncertainties in rockfall source areas identification.

Calibration of UAV Flight Parameters to Inspect the Deterioration of Heritage Façades Using Orthogonal Arrays

Heritage façades are relevant to the historical preservation and identity of a city. Their deterioration can cause the devaluation of the urban environment, together with accidents caused by possible detachment of their different elements; therefore, maintaining them is crucial. It is important to have early warning systems in place, systems which would indicate potential damage and deterioration of such façades, which can be caused by factors such as humidity, earthquakes, the passage of time, or even people. This is often done through visual inspection; however, visual inspection is often affected by external factors, such as the financing of the on-site inspection and the availability of experts. Unmanned aircraft vehicles (UAVs) are a practical and economical tool that has facilitated and improved imaging by regulating parameters such as camera angle, capture distance and image overlap, thus allowing improvements in photogrammetry techniques for virtual reconstruction processes. Although the implementation of this technology has been studied in recent years, research has focused primarily on horizontal structures, such as roads. In the case of vertical structures, flight parameters are traditionally defined by trial and error, without any methodological procedure. Therefore, this paper proposes a methodology to calibrate UAV flight parameters to build a photogrammetric 3D model of a vertical structure. This proposal is based on the development of a series of experiments configured through Taguchi orthogonal arrays, which is a method that significantly reduces the number of experiments required. This methodology is applied to a case study of a façade with architectural heritage features. The results obtained offer a flight plan and the optimal parameters to achieve efficiency in the capture of images in an inspection of heritage façades, thus achieving the optimisation of resources and time.

Volumetric Comparison Between CT Scans and Smartphone-Based Photogrammetry in Patients Undergoing Chin Augmentation With Autologous Fat Graft.

The most accurate methods for assessing fat grafted volume, such as computed tomography (CT) scan and magnetic resonance imaging, use 3-dimensional (3D) evaluation of the recipient area. Currently, other measurement techniques such as photogrammetry (compilation of photos) are employed. The aim of the present study was to compare 3D images obtained by CT scan with those obtained by photogrammetry in patients undergoing autogenous fat grafting to the chin. A prospective longitudinal study was undertaken to assess patients undergoing autologous fat grafting to the chin, capturing preoperative and postoperative (6 months) images with CT scan and photogrammetry. Captured images were submitted to 3D reconstruction with Blender image software. A total of 40 patients were submitted to surgery. Seventy-five percent were female. Median age and BMI were 26.5 years and 23.6 kg/m2, respectively. Median volume of fat grafted was 10 mL (interquartile range 8-12.25 mL). Results showed that the median preoperative volume measured by CT scan was larger than the photogrammetry measurement (12.48 mL vs 12.01 mL, respectively, P < .001). Likewise, a larger volume was measured by CT scan than by photogrammetry (15.54 mL vs 14.94 mL respectively, P < .001) 6 months postoperatively. However, there was no difference between CT scan and photogrammetry measurements of the change in volume from preoperatively to postoperatively (P = .89). There was no agreement between fat graft volume measurements obtained by 3D photogrammetry and CT scan techniques with regard to absolute values of fat graft volume measurements, however no difference was found between the 2 methods when comparing preoperative with postoperative fat graft volume variation.

Two-dimensional motion estimation using phase-based image processing with Riesz transform

As a kind of photogrammetry technique, phase-based motion estimation (PME) has proven to be a powerful image/video processing algorithm in the extraction of structural dynamics, due to its full-filed resolution and no requirement of surface preparation, compared to conventional structural testing. Although images and videos employed in PME are two-dimensional arrays, PME only extracts phase information in a single direction at a time. Therefore, extracting two-directional motions at the same time is needed to avoid two times of PME implementation. To address this issue, Riesz-transform is integrated to the phase-based motion estimation algorithm, and Riesz transform PME (RPME) is proposed in this work. The concept of plane phase is extended to spatial phase using Riesz transform to process images, because Riesz transform is able to extract phase information in two directions simultaneously. Then quaternion is utilized to derive the theoretical relationship between spatial phase and structure motions. In order to obtain the mono-component image sequence required in Riesz transform, an ideal narrow bandpass filter is constructed based on the set of Butterworth low-pass filters. Due to the capability of recognizing two-directional motions simultaneously using the proposed RPME, a much-improved efficiency of structural dynamics identification is observed. In addition, Riesz transform extracts instantaneous phase, thus the motion recognition accuracy is improved as well. To validate the benefit of RPME, both numerical simulation and laboratory-scale experiments are conducted, and motions in x and y directions are extracted simultaneously, with a drastically increased accuracy in both the simulation and experimental validations.

Preliminary assessment of joint roughness coefficient of rock slope using close-range photogrammetry technique

Rock shear strength can be estimated using the Barton–Bandis model, which relies on the joint roughness coefficient (JRC). The Barton comb profilometer is widely used in the field. However, it requires much labor. It is also difficult to access and potentially dangerous. As far as we know, no comprehensive work is dedicated to determining the JRC of the rock block sample using the image analysis technique. The JRC measurement results are compared with the manual Barton comb profilometer results to determine the reliability of the close-range photogrammetry (CRP) technique. This photogrammetry technique is applied to measure the JRC of the rock slope in the study area. Using the CRP method, a drone (DJI Phantom 4 Pro) captures a high-resolution image of the rock slope. The JRC of the rock slope is digitized through image processing to create a three-dimensional model comprising four quality ratings: low, medium, high, and ultrahigh. The ultrahigh quality has the most accurate measurement among all the quality ratings. It has a 0% error compared with the actual measurement using the Barton comb, whereas low, medium, and high qualities have 15.54%, 9.46%, and 2.7% errors, respectively. However, the medium quality is the most efficient because it can produce a reliable JRC measurement within a short period and can be used for fieldwork.

A novel approach to investigating 3D fracture connectivity in ultrahigh steep rock slopes

Ensuring the high-quality construction of the ST Railway is a top priority for construction organizers and managers. In this paper, a stepwise approach combining bounding box (BB) technology and the Gilbert–Johnson–Keerthi (GJK) algorithm was proposed to determine the intersections between fractures. With the use of a stepwise approach, most of the nonintersecting fracture pairs were excluded, the computed speed and effectiveness were greatly improved compared with those in previous studies, and the length and direction vectors of the fracture intersections were obtained. A 3D discrete fracture network (DFN) model was generated and validated according to fracture data acquired from the right bank slope of the Nujiang Grand Bridge (NGB) of the ST Railway by unmanned aerial vehicle (UAV) photogrammetry technique. Based on the DFN model, the stepwise approach was implemented for intersection analysis and connectivity analysis. Connectivity parameters, including the number of intersections per unit volume and the intersection length per unit volume, were calculated as 1.279 m-3 and 2.296 m-2, respectively. The intersection analysis suggested that the mean length of the intersections was 1.796 m, and fracture sets 2 and 3 constituted the main flow pathways and played a predominantly combined cutting role for the rock masses in the study area. In addition, the investigation of the direction vector of the intersections indicated that the combined cutting action of fracture sets 2 and 3 easily formed wedge-shaped failure surfaces, and the lateral expansion produced by bedrock fracture groundwater was also unfavourable to the stability of the slope.

3D DIGITIZATION OF HERITAGE: PHOTOMETRIC STEREO CAN HELP

Abstract. There are mainly two families of photographic 3D reconstruction. Photogrammetry techniques work according to the principle of triangulation, from the matching of different views, while photometric techniques link the appearance of a 3D point to the orientation of its normal, relative to the direction of the incident light. While photogrammetry allows to find the global shape of a 3D scene, if it is sufficiently textured, photometric techniques highlight the details of the relief, as long as the model linking the lighting to the shape and reflectance of the scene is sufficiently realistic. In order to avoid errors in the 3D models obtained, all the photographic techniques of 3D reconstruction have benefited, over the years, from algorithmic improvements that make them more and more robust to outliers or unreliable data. Moreover, the complementarity between these two types of approaches having been identified for a long time, many solutions have been proposed to merge them. Our work aims at providing the free and open-source photogrammetry software Meshroom with the benefits it could get from photometric stereo, particularly in the context of the 3D digitization of heritage, knowing that it is the only photometric technique for 3D reconstruction that has really proven itself.

Integrating Laser-induced breakdown spectroscopy and photogrammetry towards 3D element mapping

The possibility to map the element distribution on a sample surface is one of the interesting applications of laser-induced breakdown spectroscopy that has been extensively explored in recent years. In this manuscript, we explore the combination of photogrammetry and LIBS techniques for the creation of a three-dimensional model of the map of the elements on the surface of the sample. Using a dedicated photogrammetry solution and software, we reconstruct the three-dimensional model of the mineral sample whose mesh is later exploited for the interactive interpretation of the results. Then, making use of Paraview software, which integrates production algorithms and computing performance in a unified solution for scientific purposes, we establish a process pipeline that allows the creation of an interactive three-dimensional model with the spatial distribution of the target elements on top of the sample surface. Our results demonstrate that combining these two techniques can give us a valuable resource for better qualitative analysis and insight, providing an innovative three-dimensional modeling solution that may open the door to a new range of possibilities, from quality control technology involving alloys and mechanical parts to interactive teaching environments for geo and biosciences, just to name a few examples.

Spatial Distribution Pattern of Root Sprouts under the Canopy of Malus sieversii in a Typical River Valley on the Northern Slopes of the Tianshan Mountain

Malus sieversii is a precious wild fruit tree resource, and its sustainable reproduction is of great significance to the conservation of wild fruit tree germplasm resources and the stability of wild fruit forest ecosystems. In recent years, the natural population number and area of distribution of the Malus sieversii have been declining due to pests, water limitations, and human activities. Root sprouts are a primary means of rejuvenation of the Malus sieversii. A reasonable spatial distribution pattern is conducive to the growth of Malus sieversii plants and the ecological restoration of wild fruit forest populations. However, the spatial distribution pattern of root sprouts still needs to be discovered, which constrains our understanding of the mechanisms underlying the damage and management of Malus sieversii. Therefore, this paper examines the study area of the Gilgalang River Malus sieversii forest in Gongliu County, Ili Valley, Xinjiang. The topographic data and high-resolution images were first obtained using ultra-low-altitude photogrammetry and total station measurement techniques, then spatial pattern analysis and standard deviation ellipse analysis were used to investigate the spatial distribution pattern of root sprouts, and, finally, the factors affecting the spatial distribution pattern of root sprouts were investigated by principal component analysis and grey correlation analysis. The results show that: (1) Under-canopy Malus sieversii root sprouts are clustered and randomly distributed along the root system, with the degree of clustering decreasing with increasing distance; (2) Spatial orientation and distance from the maternal plant are the main factor affecting the sprouting of Malus sieversii roots, explaining 73.69% of the total variance; (3) Under sediment accumulation and water erosion, the root sprouts under the canopy are mainly distributed in the downslope direction. The shape is similar to the “clover type”. The results of this study can provide a theoretical basis for conserving Malus sieversii germplasm resources and a solid scientific basis for the ecological restoration of plants under anthropogenic disturbance.

Analysis of the Influence of the Geometrical Parameters of the Body Scanner on the Accuracy of Reconstruction of the Human Figure Using the Photogrammetry Technique

This article concerns the research of the HUBO full-body scanner, which includes the analysis and selection of the scanner's geometrical parameters in order to obtain the highest possible accuracy of the reconstruction of a human figure. In the scanner version analyzed in this paper, smartphone cameras are used as sensors. In order to process the collected photos into a 3D model, the photogrammetry technique is applied. As part of the work, dependencies between the geometrical parameters of the scanner are derived, which allows to significantly reduce the number of degrees of freedom in the selection of its geometrical parameters. Based on these dependencies, a numerical analysis is carried out, as a result of which the initial values of the geometrical parameters are pre-selected and distribution of scanner cameras is visualized. As part of the experimental research, the influence of selected scanner parameters on the scanning accuracy is analyzed. For the experimental research, a specially prepared dummy was used instead of the participation of a real human, which allowed to ensure the constancy of the scanned object. The accuracy of the object reconstruction was assessed in relation to the reference 3D model obtained with a scanner of superior measurement uncertainty. On the basis of the conducted research, a method for the selection of the scanner's geometrical parameters was finally verified, leading to the arrangement of cameras around a human, which guarantees high accuracy of the reconstruction. Additionally, to quantify the results, the quality rates were used, taking into account not only the obtained measurement uncertainty of the scanner, but also the processing time and the resulting efficiency.

The relation of forward head posture with back muscle endurance in primary school children: a cross-sectional study

BackgroundThe goal of this study was to look at the correlation between forwarding head posture and back muscle endurance in 288 primary school healthy active children aged 7–10 years old in public schools in Sheblanga, Benha, Qalubyia governorate (170 boys and 118 girls).MethodsA cross-sectional study was conducted on elementary school children to see whether there was a link between forwarding head posture and back muscle endurance. The photogrammetry technique of craniovertebral angle (CVA) was employed to quantify forward head position, and the Biering Sorensen test was utilized to evaluate isometric back muscle endurance.ResultsThe distribution of head posture in the study group revealed 132 (46%) children with advancing head posture and 156 (54%) children with normal posture. In the study group, the connection between CVA and trunk extensor endurance was moderately significant (r = 0.4, p = 0.0001). The trunk extensor endurance of children with advancing heads was significantly lower than that of children with normal postures (p = 0.0001).ConclusionsThere is a link between forwarding head posture (FHP) and back muscle endurance.