An approach to interesting objects detection in low quality image sequences for fisheries management
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Authors
Li, Z.
Chen, L.
Peng, J.
Song, Lei
Chen, L.
Peng, J.
Song, Lei
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Date
2015
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Type
Journal Article
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
low quality image processing
image processing
features extraction
interest objects
fisheries management
image processing
features extraction
interest objects
fisheries management
ANZSRC Field of Research Code (2020)
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.
Abstract
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%
Publisher
World Scientific and Engineering Academy and Society (WSEAS)
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Attribution 4.0 International