The recent developments in underwater video monitoring system makes automatic object detection and object tracking a significant and challenging task. In such processing, the method involves preprocessing, feature extraction, object classification, object detection and tracking. Detecting moving objects from the underwater video has many potential applications for Remotely Operated Vehicles (ROVs) or Autonomous Underwater Vehicles (AUVs), such as tracking fish, recognizing underwater objects etc. Underwater object recognition is a cumbersome due to the change in water structure, seasonal, climatic changes, temperature variation and further degraded by a poor non-uniform source of artificial light. Diverse approaches using image processing and pattern recognition have been proposed by numerous scientists and marine engineers to tackle these problems using methods such as neural network, contour matching, and statistical analysis. In this article, we provide a comprehensive overview of different methods and techniques of object detection and object tracking in general and underwater scenario in particular. We have been successful in highlighting the several key features and aspects of underwater object detection and tracking which will take the work in this domain further.

Underwater image enhancement, Object Detection, Tracking, Recognition and Machine Learning

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