فهرست نشریات علمی دسترسی آزاد ایران

Detecting and preventing incidents with obstacles is a challenging problem. Most of the common obstacledetection techniques are currently sensor-based. Mobile robots like Small Unmanned Aerial Vehicles(UAVs) are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods areconsidered, which can be divided into stereo and mono techniques. Mono methods are classified into twogroups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods arehighly efficient in obstacle detection. A recent research in this field has focused on matching the ScaleInvariant Feature Transform (SIFT) points along with SIFT size-ratio factor and area-ratio of convex hullsin two consecutive frames to detect obstacles. However, this method is not able to distinguish betweennear and far obstacles nor the obstacles in a complex environment and, thus, is sensitive to wrong matchedpoints. This paper aims to solve the aforementioned problems through using the distance-ratio of matchedpoints. Then, every point is investigated for distinguishing between far and near obstacles. The resultsdemonstrated the high efficiency of the proposed method in complex environments. The least achievedaccuracy of the algorithm was 60.0%, and the overall accuracy was 79.0%.