Object detection in infrared image with sea clutter

Abstract

In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analyzing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by an adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

Obstacle Avoidance Approaches for Autonomous Navigation of Unmanned Surface Vehicles

“…Without specifying any details about the target object, this approach detects every anomaly in respect to the background. IR data are also used in Park and Jeong (2012), where a multi-step algorithm extracts the shape of a floating object. Vertical and horizontal edges are initially extracted to find candidate objects.…”