科研之友
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摘要
In complex underwater situations, how to realize object extraction accurately and effectively is the key technology of underwater object recognition. In this paper, the detection and recognition techniques of underwater man-made objects on the basis of color and shape features have been studied in depth. First, the objects of interest in an underwater image are extracted by applying a color-based algorithm. Then an improved two-dimensional Otsu algorithm is utilized for removing the background color noise. To recognize the shape type of a regular object, a robust algorithm based on shape signature is presented. The experimental results show that the proposed approach is effective and robust, such as an acceptable extraction rate (exceeding 80%) of the object of interest, an ideal outcome of background color noise removal, high accurate shape of the object's edge, and a good average recognition rate of shape type (approximately 90%). It proves that this algorithm can accurately settle the problem of object extraction and recognition under different cases of distance, angle, and illumination.
