An approach to interesting objects detection in low quality image sequences for fisheries management
Li, Z.; Chen, L.; Peng, J.; Song, Lei
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Citation:Li, Zuojin., Chen, Liukui., Peng, Jun., & Song, Lei. (2015). An Approach to Interesting Objects Detection in Low Quality Image Sequences for Fisheries Management. WSEAS Transactions on Signal Processing, 11, 1-8.
Permanent link to Research Bank record:https://hdl.handle.net/10652/5665
In order to extract interest objects in low quality image sequences from fisheries management, this paper proposes a new significant feature extraction method based on cascade framework. This algorithm involves pre processing image sequences, clipping interesting areas, extracting SURF features, removing boundary features, and acquiring significant features with interesting objects. We apply our algorithm to fisheries management for counting and matching ships and cars, the proposed method can efficiently detect multiple objects from real-scene video frames with averaged accuracy 91.63%
Keywords:low quality image processing, image processing, features extraction, interest objects, fisheries management
ANZSRC Field of Research:460306 Image processing, 300505 Fisheries management
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