**6.1 Integration of 3D processing operations**

The 3D processing layer contains all relevant aspects related to the 3D processing algorithms. Its integration into the suggested semantic framework is done by special Built-Ins. They manage the interaction between processing layers and the semantic one. In addition, it contains the different algorithm definitions, properties, and the related geometries to the each defined algorithms. An importance achievement is the detection and the identification of objects with specific characteristics such as a signal, indicator columns, and electric pole, etc. through utilizing their geometric properties. Since the information in point cloud data sometimes is unclear and insufficient, the Semantic Web Rule Language within extended builtins is used to execute a real 3D processing algorithm, and to populate the provided knowledge within the ontology (e.g. Table 4). The equation 2 illustrate the "3D\_swrlb\_Processing: VerticalElementDetection" built-ins for example, it aims at the detection of geometry with vertical orientation. The prototype of the designed Built-in is:

3D\_swrlb\_Processing:VerticalElementDetection(?Vert, ?Dir) (2)

Where the first parameter presents the target object class, and the last one presents the point clouds' directory defined within the created scene in the ontology structure. At this point, the detection process will result bounding boxes, representing a rough position and orientation of the detected object. Table 4 shows the mapping between the 3D processing built-ins, which is computer and translated to predicate, and the corresponding class.


Table 4. 3D processing Built-Ins mapping.

236 Semantics – Advances in Theories and Mathematical Models

The following section presents in details the semantic integration process undertaken in the

The basic strength of formal ontology is their ability to reason in a logical way based on Descriptive Logic language DL. As seem, the last one presents a form of logic to reason on objects. Lots of reasoners exist nowadays like Pellet (Sirin, et al., 2007), and KAON (U. Hustadt, 2010). Actually, despite the richness of OWL's set of relational properties, the axioms does not cover the full range of expressive possibilities for object relationships that we might find, since it is useful to declare relationship in term of conditions or even rules. These rules are used through different rules languages to enhance the knowledge possess in

Within the actual research, the domain ontologies are used to define the concepts, and the necessary and sufficient conditions on them. These conditions are of value, because they are used to populate new concepts. For instance, the concept Goem:Vertical\_BoudinBox can be specialized into DC:Signal if it contains a Goem:VerticalLines. Consequently, the concept DC:Signal will be populated with all Goem:Vertical\_BoudinBox if they are linked to a Goem:VerticalLines with certain parameters. In addition, the rules are used to compute more complex results such as the topological relationships between objects. For instance, the relations between two objects are used to get new efficient knowledge about the object. The ontology is than enriched with this new relationship. The topological relation built-ins are not defined in the SWRL language. Consequently, the language was extended. To support the defined use cases, two basic further layers to the semantic one are added to ontology in order to ensure the geometry detection and annotation process tasks. These operations are the 3D

The 3D processing layer contains all relevant aspects related to the 3D processing algorithms. Its integration into the suggested semantic framework is done by special Built-Ins. They manage the interaction between processing layers and the semantic one. In addition, it contains the different algorithm definitions, properties, and the related geometries to the each defined algorithms. An importance achievement is the detection and the identification of objects with specific characteristics such as a signal, indicator columns, and electric pole, etc. through utilizing their geometric properties. Since the information in point cloud data sometimes is unclear and insufficient, the Semantic Web Rule Language within extended builtins is used to execute a real 3D processing algorithm, and to populate the provided knowledge within the ontology (e.g. Table 4). The equation 2 illustrate the "3D\_swrlb\_Processing: VerticalElementDetection" built-ins for example, it aims at the detection of geometry with

 3D\_swrlb\_Processing:VerticalElementDetection(?Vert, ?Dir) (2) Where the first parameter presents the target object class, and the last one presents the point clouds' directory defined within the created scene in the ontology structure. At this point,

processing and topological relations qualification respectively.

vertical orientation. The prototype of the designed Built-in is:

**6.1 Integration of 3D processing operations** 

WiDOP solution to detect and annotate semantically the eventual semantic elements.

**6. Intelligent process** 

an ontology.
