Algorithms and their applications:

• A quantitative quality measure approach for 3D photorealistic virtual models named Model Texture Quality Index MTQI has been developed to assess the overall quality of the whole model’s texture. The approach applied a new metric that has been proposed to be employed in the presented MTQI approach. To validate the MTQI approach, the texture quality of three real models has been measured using the approach. They are also investigated visually by subjects including experienced archaeologists. The results show a consistent correlation.

Published in Nov. 2018, Survey Review Journal; University of the West of England, United Kingdom.

DOI: https://doi.org/10.1080/00396265.2018.1543928, IF: 1.163.

• A two points registration (TPR) algorithm is developed to register terrestrial laser scanner point clouds using only two common points. By using the TPR algorithm, the time of placing artificial targets in-site and the time and the effort required for detecting targets as well as the cost of the artificial targets have been successfully reduced by one-third. The obtained registration accuracy using the TPR algorithm is comparable to the obtained accuracy using the traditional three points registration method.

Published in Jan. 2018, Survey Review Journal; University of the West of England, United Kingdom.

DOI: https://doi.org/10.1080/00396265.2017.1418787. IF: 1.163.

• An algorithm for automatic texture mapping named “Mesh Photo Mapper MPM” is developed and coded successfully. The issue requires some sort of algorithms by which the machine is learned how to imitate the human selection. It projects all triangulated faces of the 3D model on images then detects the occluded parts of each image. The algorithm considers five parameters while assigning the appropriate texture from the available images, which are texture resolution, visibility, priority, quality and compatibility with surroundings. The developed scoring algorithm is compared with the state-of-the-art algorithms by texturing the Almaqah temple 3D model using different algorithms. The comparison shows the efficiency and the reliability of the developed algorithm. It raises the automation level in texture mapping such large projects.

Published in Nov. 2018, Journal of Spatial Science. United Kingdom.

DOI: https://doi.org/10.1080/14498596.2018.1536002. IF: 1.078.

• Occlusion detection algorithm: The Multi Layer 3DImage algorithm (ML3DImage) is developed to detect various types of occlusions in a 3D scene. It serves in the automatic texture mapping work. The ML3DImage algorithm serves in the Austrian START Project “The Domitilla Catacombs in Rome: Archaeology, Architecture and History of Art of a Late Roman Cemetery”. The Project aims mainly to recover a complete 3D model for the Domitilla catacomb which is the largest catacomb in Rome.

Published in July 2009, 9th Conf. Optical 3-D Measurement Techniques, Vienna, Austria.

• Photo Occlusions Finder (POF) algorithm for removing un-modeled objects in the scene. Such un-modeled objects will not be detected by ordinary occlusion detection algorithms as un-modeled objects appear only in photos. Therefore both objects geometry and objects textures are employed in the POF algorithm. The main characteristics of this algorithm are the ability to detect various types of occlusions (modeled/un-modeled) and the flexibility to deal with different photos captured by different sensors full automatic.

Published in my PhD thesis online on Deutsche Geodätische Kommission (DGK), München 2009, (C 631).

• Algorithm of coloring point clouds (CPC) from multiple photos automatically. This can be used with registered images captured by hand-held cameras.

The CPC algorithm is used for the historical 3D heritage documentation in Borobudur temple project, Indonesia.

Published in September 2006, ISPRS commission V Symposium, Dresden, Germany.

• Scanners equipped with digital cameras deliver in one step a colored point cloud for the captured scene. After the registration step between multiple point clouds, the user obtains bad color quality. An algorithm of coloring Laser Scanner point cloud LPC is developed in order to reprocess the merged point clouds again to get the desired good color quality. Using such pipeline will lead to simplify the work flow of documentation which will give the chance for more historical sites to be documented.

The LPC algorithm is used to recover the Ephesos in Turkey which is the most scenic historic excavation site.

Published in 2013, Survey Review Journal, University of the West of England, United Kingdom,

DOI: https://doi.org/10.1179/1752270612Y.0000000031.

Multi-sensors data fusion:

• Thermal images are fused with the laser scanner point cloud and digital photos in what is called Thermal3DImage. Within the framework of energy saving in Europe, each building has to fulfill thermal insulation requirements to get permission for further use through what is called an “Energy passport”. By using Thermal3DImage in buildings maintenance, on can detect air leakage (heat/cold) coming from buildings openings (doors and windows). Afterwards, the amount of (heat/cold) air can be computed to be checked against accepted limits. Early detection of any expected water seepage that may occur inside building walls. The exact location of the defected parts can then be determined and subsequently the area influenced by the water seepage can be computed.

Published in 2013, Survey Review Journal, University of the West of England, United Kingdom,

DOI: https://doi.org/10.1179/1752270612Y.0000000002.

The laser scanner point cloud and digital photos are also combined in what is called 3DImage.

Published in August 2005, International workshop 3DArch, Mestre-Venice, Italy.

Image processing and remote sensing:

• Shadow detection is an active field of research. Shadow detection approaches are divided into two main categories, the first is the model-based approach. This requires a priori knowledge of the environmental conditions. The shadow areas are calculated here according to the geometric features in the image, the height of sun angle, the remote sensor, and other relevant parameters. The pixel-based approach represents the second category. This makes use of certain image shadow properties such as colour (or intensity), shadow structure, and boundaries, with no assumptions about the scene structure. A shadow detector index (SDI) is developed to classify high resolution satellite images with an automatic threshold identification procedure. The whole approach is applied on different study areas and high accuracies are achieved (average of 97%).

Published in 2017, IEEE Geoscience and Remote Sensing Letters.

DOI: 10.1109/LGRS.2017.2650996. IF: 2.892.

• The Issue of classifying water and shadow as shadow in high resolution satellite images requires also a solution. This problem leads to misidentification of water pixels as shadow. A new image index based on the RGB channels is developed. The histogram of this index separates non shadow, shadow, and water pixels with around 93% as overall accuracy.

Published in Feb. 2017, Photogrammetric Engineering & Remote Sensing journal, American Society for Photogrammetry and Remote Sensing.

DOI: https://doi.org/10.14358/PERS.83.2.87. IF: 3.15.

• On the other hand, the infrared channel is also employed in another shadow detection approach to differentiate between water and shadow. Around 94% overall accuracy is achieved.

Published in Nov. 2015, International Journal of Remote Sensing,

DOI: https://doi.org/10.1080/01431161.2015.1112930, IF: 1.782.

Risk assessment

• The RAM lab funded by the science and technology development STDF organization aims mainly to develop a center of excellence in some modern and interdisciplinary fields. The main goal is to establish an application strategy for risk assessment and documentation of Egyptian monuments and ancient structure using state of the art 3D technologies (laser scanning, thermal photogrammetry and FEM analysis). The lab also offers training courses and consultancy for relevant organizations.

Published in Heritage 2016, 5^th international Conference on Heritage and Sustainable Development, Lisbon.

Hybrid Imaging Techniques for the Assessment of Thermal Insulation Effect of Green Materials on Green Buildings in KSA

• Energy saving is a catch word in the last two decades and it is expected to be in the coming decades. Buildings consumption sector in KSA has proved to consume high percent of the total electricity generated. Thermal insulation reduces buildings energy consumption from 30 to 40 percent. An approach is proposed to give a definite value for the efficiency of building insulation based on computations rather than visual interpretation used in KSA. The computations depend on measuring the inside and outside temperatures for the building envelope by means of thermography. Digital images are also required for the visual scene. A data fusion process is therefore required to achieve the insulation efficiency degree. The project is proposed to provide us with the accepted insulation reference values and the optimum method for decision making.