Target Detection and Tracking Based on Ship Borne Infrared Imagery

Abstract

A novel automatic target detection and tracking algorithm for tracking targets based on ship borne infrared imagery is proposed in this paper. The algorithm has two modes: detection and tracking. In detection mode, the proposed algorithm utilized difference between the consecutive frames and top-hat filter to determine the target position. In tracking mode, the Intensity Variation Function (IVF) is utilized. Before tracking and location the new position, the algorithm should determine the IVF whether reliable. If unreliable, the mode turns to detection. Experimental results by using real-life infrared image sequence are shown to validate the robustness of the proposed technique.

Thermal Infrared Small Ship Detection in Sea Clutter Based on Morphological Reconstruction and Multi-Feature Analysis

“…In this part, four classical ship target detection methods and four state-of-the-art ship target detection methods are introduced in the comparison experiments to evaluate the performance of the proposed TIR ship target detection method. The top-hat/bot-hat filters (THF/BHF) [6,35], 2-D maximum entropy (2DME) [17], 2-D Otsu (2DO) [15] and mean shift segmentation (MSS) [19] are chosen as representative classical ship target detection methods. The iterative multi-feature segmentation (IMFS) [23], improved fuzzy C-means clustering (IFCM) [3], Chan-Vese model (CVM) [21] and histogram cyclic shift transformation (HCST) [13] are selected as representative state-of-the-art methods.…”

“…therefore, the THF extracts bright interesting regions and BHF highlights dark interesting regions in image f . In TIR ship image, the ship target is usually a bright (dark) region, so THF/BHF can be directly used to detect ship targets [6,35]. For infrared ship image with high SCR, the classical THF/BHF filters can achieve good detection performance.…”

“…The representative TIR ship detection algorithms can be roughly divided into two categories, namely, detect-before-track (DBT) strategy and track-before-detect (TBD) strategy. By taking full advantage of the continuity of moving target and the stationarity of background, the TBD-based detection methods, such as frame difference method [6], three-plot correlation filter [7] and multi-stage hypothesis test filter [8], have achieved outstanding performance for the ships with continuous trajectory. However, in many maritime scenes, the background is changeable, and the target trajectory might be discontinuous, so the performance of TBD methods would degrade sharply.…”

Detect ships using saliency in infrared images with sea-sky background

“…In recent years, ship detection in infrared images with sea-sky background attracts increasing attention. Many methods are proposed in this field, including image segmentation methods [1][2] and morphological methods [3]. However, due to complex sea-sky environment and large variation of ship sizes, these methods cannot solve the issue completely.…”