Influence of illumination changes on image-based 3D surface reconstruction

The paper investigates the influence of lighting conditions on image-based 3D surface reconstruction, with particular focus on periodic photogrammetric surveys for monitoring and 3D mapping applications. The analyses focus on the accuracy and completeness of each DSM and the daily and hourly repeatability of repeated photogrammetric surveys. Three test sites with rock slopes with a different orientation to the sun and different slope characteristics (slope, pattern, amount of outcropping elements that cast shadows) have been considered to ensure that results can give a general indication of the behaviours in different light conditions. In addition, a simulated virtual test site is included in the study to allow controlled image acquisition and evaluate the effect of the sun's inclination on the DSM accuracy without influence of other weather conditions. The results show that, although there is an optimal time for the acquisitions, if particularly unfavourable light conditions are excluded, the accuracy reduction with time variation is always below 30%. The repeatability analyses by day and by time highlight a good consistence between DEMs belonging to the same day but acquired at different times and, also, between DEMs acquired at the same time but on different days. This suggests that reliable results can be obtained during continuous monitoring of, for instance, rock faces to identify rockfalls

Photogrammetric digital surface model reconstruction in extreme low-light environments

Digital surface models (DSM) have become one of the main sources of geometrical information for a broad range of applications. Image-based systems typically rely on passive sensors which can represent a strong limitation in several survey activities (e.g., night-time monitoring, underground survey and night surveillance). However, recent progresses in sensor technology allow very high sensitivity which drastically improves low-light image quality by applying innovative noise reduction techniques. This work focuses on the performances of night-time photogrammetric systems devoted to the monitoring of rock slopes. The study investigates the application of different camera settings and their reliability to produce accurate DSM. A total of 672 stereo-pairs acquired with high-sensitivity cameras (Nikon D800 and D810) at three different testing sites were considered. The dataset includes different camera configurations (ISO speed, shutter speed, aperture and image under-/over-exposure). The use of image quality assessment (IQA) methods to evaluate the quality of the images prior to the 3D reconstruction is investigated. The results show that modern high-sensitivity cameras allow the reconstruction of accurate DSM in an extreme low-light environment and, exploiting the correct camera setup, achieving comparable results to daylight acquisitions. This makes imaging sensors extremely versatile for monitoring applications at generally low costs

Analysis of low-light and night-time stereo-pair images for photogrammetric reconstruction

Rockfalls and rockslides represent a significant risk to human lives and infrastructures because of the high levels of energy involved in the phenomena. Generally, these events occur in accordance to specific environmental conditions, such as temperature variations between day and night, that can contribute to the triggering of structural instabilities in the rock-wall and the detachment of blocks and debris. The monitoring and the geostructural characterization of the wall are required for reducing the potential hazard and to improve the management of the risk at the bottom of the slopes affected by such phenomena. In this context, close range photogrammetry is largely used for the monitoring of high-mountain terrains and rock walls in mine sites allowing for periodic survey of rockfalls and wall movements. This work focuses on the analysis of low-light and night-time images of a fixed-base stereo pair photogrammetry system. The aim is to study the reliability of the images acquired over the night to produce digital surface models (DSMs) for change detection. The images are captured by a high-sensitivity DLSR camera using various settings accounting for different values of ISO, aperture and time of exposure. For each acquisition, the DSM is compared to a photogrammetric reference model produced by images captured in optimal illumination conditions. Results show that, with high level of ISO and maintaining the same grade of aperture, extending the exposure time improves the quality of the point clouds in terms of completeness and accuracy of the photogrammetric models

Preliminary tests of a new low-cost photogrammetric system

This paper presents preliminary tests of a new low-cost photogrammetric system for 4D modelling of large scale areas for civil engineering applications. The system consists of five stand-alone units. Each of the units is composed of a Raspberry Pi 2 Model B (RPi2B) single board computer connected to a PiCamera Module V2 (8 MP) and is powered by a 10 W solar panel. The acquisition of the images is performed automatically using Python scripts and the OpenCV library. Images are recorded at different times during the day and automatically uploaded onto a FTP server from where they can be accessed for processing. Preliminary tests and outcomes of the system are discussed in detail. The focus is on the performance assessment of the low-cost sensor and the quality evaluation of the digital surface models generated by the low-cost photogrammetric systems in the field under real test conditions. Two different test cases were set up in order to calibrate the low-cost photogrammetric system and to assess its performance. First comparisons with a TLS model show a good agreement

PRELIMINARY TESTS OF A NEW LOW-COST PHOTOGRAMMETRIC SYSTEM

This paper presents preliminary tests of a new low-cost photogrammetric system for 4D modelling of large scale areas for civil engineering applications. The system consists of five stand-alone units. Each of the units is composed of a Raspberry Pi 2 Model B (RPi2B) single board computer connected to a PiCamera Module V2 (8 MP) and is powered by a 10 W solar panel. The acquisition of the images is performed automatically using Python scripts and the OpenCV library. Images are recorded at different times during the day and automatically uploaded onto a FTP server from where they can be accessed for processing. Preliminary tests and outcomes of the system are discussed in detail. The focus is on the performance assessment of the low-cost sensor and the quality evaluation of the digital surface models generated by the low-cost photogrammetric systems in the field under real test conditions. Two different test cases were set up in order to calibrate the low-cost photogrammetric system and to assess its performance. First comparisons with a TLS model show a good agreement

A comparison of low-cost cameras applied to fixed multi-image monitoring systems

Photogrammetry is becoming a widely used technique for slope monitoring and rock fall data collection. Its scalability, simplicity of components and low costs for hardware and operations makes its use constantly increasing for both civil and mining applications. Recent on site permanent installation of cameras resulted particularly viable for the monitoring of extended surfaces at very reasonable costs. The current work investigates the performances of a customised Raspberry Pi camera module V2 system and three additional low-cost camera systems including an ELP-USB8MP02G camera module, a compact digital camera (Nikon S3100) and a DSLR (Nikon D3). All system, except the Nikon D3, are available at comparable price. The comparison was conducted by collecting images of rock surfaces, one located in Australia and three located in Italy, from distances between 55 and 110 m. Results are presented in terms of image quality and three dimensional reconstruction error. Thereby, the multi-view reconstructions are compared to a reference model acquired with a terrestrial laser scanner

Temporal-spatial frequency rockfall data from open-pit highwalls using a low-cost monitoring system

In surface mining, rockfall can seriously threaten the safety of personnel located at the base of highwalls and cause serious damage to equipment and machinery. Close-range photogrammetry for the continuous monitoring of rock surfaces represents a valid tool to efficiently assess the potential rockfall hazard and estimate the risk in the affected areas. This work presents an autonomous terrestrial stereo-pair photogrammetric monitoring system developed to observe volumes falling from sub-vertical rock faces located in surface mining environments. The system has the versatility for rapid installation and quick relocation in areas often constrained by accessibility and safety issues and it has the robustness to tolerate the rough environmental conditions typical of mining operations. It allows the collection of synchronised images at different periods with high-sensitivity digital single-lens reflex cameras, producing accurate digital surface models (DSM) of the rock face. Comparisons between successive DSMs can detect detachments and surface movements during defined observation periods. Detailed analysis of the changes in the rock surface, volumes and frequency of the rocks dislodging from the sub-vertical rock surfaces can provide accurate information on event magnitude and return period at very reasonable cost and, therefore, can generate the necessary data for a detailed inventory of the rockfall spatial-temporal occurrence and magnitude. The system was first validated in a trial site, and then applied on a mine site located in NSW (Australia). Results were analysed in terms of multi-temporal data acquired over a period of seven weeks. The excellent detail of the data allowed trends in rockfall event to be correlated to lithology and rainfall events, demonstrating the capability of the system to generate useful data that would otherwise require extended periods of direct observation

PRELIMINARY TESTS OF A NEW LOW-COST PHOTOGRAMMETRIC SYSTEM

This paper presents preliminary tests of a new low-cost photogrammetric system for 4D modelling of large scale areas for civil engineering applications. The system consists of five stand-alone units. Each of the units is composed of a Raspberry Pi 2 Model B (RPi2B) single board computer connected to a PiCamera Module V2 (8 MP) and is powered by a 10 W solar panel. The acquisition of the images is performed automatically using Python scripts and the OpenCV library. Images are recorded at different times during the day and automatically uploaded onto a FTP server from where they can be accessed for processing. Preliminary tests and outcomes of the system are discussed in detail. The focus is on the performance assessment of the low-cost sensor and the quality evaluation of the digital surface models generated by the low-cost photogrammetric systems in the field under real test conditions. Two different test cases were set up in order to calibrate the low-cost photogrammetric system and to assess its performance. First comparisons with a TLS model show a good agreement

Preoperative computed tomography staging of nonmetastatic colon cancer predicts outcome: implications for clinical trials

Colon cancer patients routinely undergo preoperative computed tomography (CT) scanning, but local staging is thought to be inaccurate. We aimed to determine if clinical outcome could be predicted from radiological features of the primary tumour. Consecutive patients at one hospital undergoing primary resection for colon cancer during 2000–2004 were included. Patients with visible metastases were excluded. Preoperative CT scans were reviewed independently by two radiologists blinded to histological stage and outcome. Images of the primary tumour were evaluated according to conventional TNM criteria and patients were stratified into ‘good' or ‘poor' prognosis groups. Comparison was made between prognostic group and actual clinical outcome. Hundred and twenty-six preoperative CT scans were reviewed. T-stage and nodal status was correctly predicted in only 60 and 62%, respectively. However, inter-observer agreement for prognostic group was 79% (κ=0.59) and 3-year relapse-free survival was 71 and 43% for the CT-predicted ‘good' and ‘poor' groups, respectively (P<0.0066). This compared favourably with 75 vs 43% for histology-predicted prognostic groups. Computed tomography is a robust method for stratifying patients preoperatively, with similar accuracy to histopathology for predicting outcome. Recognition of poor prognosis tumours preoperatively may permit investigation into the future use of neo-adjuvant therapy in colon cancer

Advanced adenoma diagnosis with FDG PET in a visibly normal mucosa: a case report

<p>Abstract</p> <p>Background</p> <p>An accurate, early diagnosis and treatment of adenomatous polyp can curtail progression to colorectal cancer. F-18 fluorodeoxyglucose positron emission tomography (F-18 FDG PET) reveals the biochemical changes associated with the development of many cancers which precede the appearance of gross anatomical changes that may be visualized during surgical resection or via imaging with MR or CT.</p> <p>Intervention</p> <p>We detail the history of a 64 year old female who had a whole-body FDG PET scan as a part of an employee wellness program. A dose of 12.2 mCi of F-18 labeled FDG was administered.</p> <p>Results</p> <p>A focal cecal uptake with a standardized uptake value (SUV) of 8.9 was found on the PET scan. Conversely, only normal mucosa was observed during a colonoscopy done 2 months after the PET scan. Motivated by the PET scan finding, the colonoscopist performed a biopsy which revealed a villous adenoma without high grade dysplasia. Pathology from tissue extracted during an exploratory laparatomy completed one month later found the lesion to be a villous adenoma with high grade dysplasia.</p> <p>Conclusion</p> <p>Whole-body FDG PET scan revealed the biochemical metabolic changes in malignancy that preceded the appearance of any gross anatomical abnormality. A positive FDG PET scan indicative of colorectal cancer should be followed up with a colonoscopy and biopsy even in a visibly normal mucosa.</p