الفهرس 
Background and Related Workيوجد فقط 14 صفحة متاحة للعرض العام
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المستخلص
The advances in sciences and technology managed to speed up many processes in our lives. In addition, it helps to develop many industries and gain high quality outputs. One of these leading industries is the concrete construction industry. This industry is rich and became a special sign of countries development. Every day, engineers help to build new civil structures or apply regularly fixes on old damaged structures. The improvements of civil constructions science and tools help to develop well-planned cities, long roads, complex and attractive bridge structures, and very tall buildings.
Citizens shall never drive on an unsafe bridge or a low-quality asphalting road. Accordingly, safety is a major factor of planning any concrete structure. Safety should be ensured during and after the construction process. Safety is satisfied by applying regular check-ups. Before millennium years, Engineers with high experience did those check-ups manually. However, manual scanning is a slow process and gives inaccurate results. Thus, the manual way has become impractical with the rapid developments of concrete structures.
To overcome manual scanning issues, technology comes in place to automate the check-up processes. Researchers and scientists in computer science have tried to implement fully automatic algorithms to allocate surface defects. Researches all over the world try to improve the allocation accuracy and make it reliable. Over the last five years, studies had successfully reached the nearly optimal results by searching for cracks with high accuracy and acceptable performance. However, the specialist intervention to analyze defect samples, calculate crack geometrical properties, and then take action according to defect severity is still needed.
Limited number of researches had worked on fetching crack characteristics instead of human specialists to support expert’s decisions. Therefore, there exists a need of researches who work on the automatic crack interpretation process in order to stop the specialists’ interventions and build fully automated systems.
In this Thesis, the importance of automatic crack detection and interpretation is discussed and then present the proposed interpretation algorithm.
The proposed algorithm in this thesis is a crack interpretation and decision-support algorithm, named region based crack interpretation algorithm. Discussing the algorithm flow chart, staring from the two individual input data sets. The algorithm starts working on the output of other crack detection algorithms accepting the input image composite of the crack as an object with white color and the background is dark black. Then, it applies the proposed image-processing algorithm to extract the crack properties per region. The region is a continuous connected line considered as a part of the crack or at some cases the whole crack. Then, it calculates the output region width, length, area, and perimeter. At last, it calculates the region severity level and the complete sample severity level. Finally, present the conclusion and the suggested future research points.
Keywords: Concrete surface defects, Automatic Crack detection, Crack interpretation, Computer aided engineers, image processing algorithm, Crack dimensions, Crack detection algorithm.