The demand for Advanced Driver Assistance System (ADAS) applications is increasing day by day and their development requires efficient prototyping and real time testing. ADTF (Automotive Data and Time Triggered Framework) is a software tool from Elektrobit which is used for Development, Validation and Visualization of Vision based applications, mainly for ADAS and Autonomous driving. With the help of ADTF tool, Image or Video data can be recorded and visualized and also the testing of data can be processed both on-line and off-line. The development of ADAS applications needs image and video processing and the algorithm has to be highly efficient and must satisfy Real-time requirements. The main objective of this research would be to integrate OpenCV library with ADTF cross platform. OpenCV libraries provide efficient image processing algorithms which can be used with ADTF for quick benchmarking and testing. An ADTF filter framework has been developed where the OpenCV algorithms can be directly used and the testing of the framework is carried out with .DAT and image files with a modular approach. CMake is also explained in this thesis to build the system with ease of use. The ADTF filters are developed in Microsoft Visual Studio 2010 in C++ and OpenMP API are used for Parallel programming approach.

The demand for Advanced Driver Assistance System (ADAS) applications is increasing day by day and their development requires efficient prototyping and real time testing. ADTF (Automotive Data and Time Triggered Framework) is a software tool from Elektrobit which is used for Development, Validation and Visualization of Vision based applications, mainly for ADAS and Autonomous driving. With the help of ADTF tool, Image or Video data can be recorded and visualized and also the testing of data can be processed both on-line and off-line. The development of ADAS applications needs image and video processing and the algorithm has to be highly efficient and must satisfy Real-time requirements. The main objective of this research would be to integrate OpenCV library with ADTF cross platform. OpenCV libraries provide efficient image processing algorithms which can be used with ADTF for quick benchmarking and testing. An ADTF filter framework has been developed where the OpenCV algorithms can be directly used and the testing of the framework is carried out with .DAT and image files with a modular approach. CMake is also explained in this thesis to build the system with ease of use. The ADTF filters are developed in Microsoft Visual Studio 2010 in C++ and OpenMP API are used for Parallel programming approach.

The APOLI project deals with Automated Power Line Inspection using Highly-automated Unmanned Aerial Systems. Beside the Real-time damage assessment by on-board high-resolution image data exploitation a postprocessing of the video data is necessary. This Master Thesis deals with the implementation of an Isolator Detector Framework and a Work ow in the Automotive Data and Time-triggered Framework(ADTF) that loads a video direct from a camera or from a storage and extracts the Key Frames which contain objects of interest. This is done by the implementation of an object detection system using C++ and the creation of ADTF Filters that perform the task of detection of the objects of interest and extract the Key Frames using a supervised learning platform. The use case is the extraction of frames from video samples that contain Images of Isolators from Power Transmission Lines.

The APOLI project deals with Automated Power Line Inspection using Highly-automated Unmanned Aerial Systems. Beside the Real-time damage assessment by on-board high-resolution image data exploitation a postprocessing of the video data is necessary. This Master Thesis deals with the implementation of an Isolator Detector Framework and a Work ow in the Automotive Data and Time-triggered Framework(ADTF) that loads a video direct from a camera or from a storage and extracts the Key Frames which contain objects of interest. This is done by the implementation of an object detection system using C++ and the creation of ADTF Filters that perform the task of detection of the objects of interest and extract the Key Frames using a supervised learning platform. The use case is the extraction of frames from video samples that contain Images of Isolators from Power Transmission Lines.