Image-based object detection and identification

Abstract

Object detection is a process of identifying and locating objects in image scene. It is a process of combining digital image processing and computer vision. There are two main approaches for object detection, namely contour-based and region-based detection for both approaches. Segmentation plays an important role in object-detection. Detection and extraction of the spatial and spectral responses of different targets of interest could only be carried out with different approaches. In this study, object-based detection is carried out to identify and recognize typical military targets (Plane1, Plane2, Tank) located on natural background using spectral and spatial approaches. This is useful in military intelligence or strategic planning where it assists in identifying the aforementioned targets. In the spectral-based object detection, the spectroradiometer readings of the targets are individually observed on different backgrounds (white platform used as calibration plane, sand and camouflage). These spectroradiometer observations are reduced and examined for forming the unique spectral signatures of the targets. Spatial-characteristics of the targets are also examined using object-based detection where multi-resolution segmentation were employed for this purpose. Results of the study obtained that all the three targets can be extracted with more than 20% differentiation, while the spectral characteristics of the targets are also good indications for object detection with overall accuracy of RMSE = ± 0.6.