| dc.description.abstract | This dissertation proposes some practical solutions for object identification based on different image acquisitions such as segmentation and classification of calcaneal fractures, detection and recognition of moving objects using an Unmanned Aerial Vehicle (UAV), and people counting applications using an RGB-D camera. In the first study, a computer-aid method for calcaneal fracture detection to acquire a faster and more detailed observation is proposed. First, the anatomical plane orientation of the tarsal bone in the input image is selected to determine the location of the calcaneus. Then, several fragments of the calcaneus image are detected and marked by color segmentation. The Sanders system is used to classify fractures in transverse and coronal images into four types based on the number of fragments. In the sagittal image, fractures are classified into three types based on the involvement of the fracture area. In the second study, a new and efficient technique is proposed for the detection and recognition of moving objects in a sequence of images captured from a UAV. First, the feature points between two successive frames are found for estimating the camera movement to stabilize the sequence of images. Then, the region of interest (ROI) of the objects are detected as the moving object candidate (foreground). Furthermore, static and dynamic objects are classified based on the most motion vectors that occur in the foreground and background. In the third study, a new technique for real-time people counting using an RGB-D camera is proposed. First, image calibration is proposed to obtain the ratio and shift values between the depth and the RGB image. In the depth image, people are detected as the foreground by removing the background. Then, the region of interest (ROI) of the detected people is registered based on their locations and is mapped to the RGB image. The registered people are tracked in the RGB image based on the discriminative correlation filter with the channel and spatial reliabilities. Finally, people are counted when they cross the line of interest (LOI) and the displacement distance is more than 2 meters. | en_US |