电子设计工程
電子設計工程
전자설계공정
ELECTRONIC DESIGN ENGINEERING
2014年
21期
138-141,148
,共5页
船体检测与跟踪%稀疏表示%K-SVD%冗余字典%马氏距离
船體檢測與跟蹤%稀疏錶示%K-SVD%冗餘字典%馬氏距離
선체검측여근종%희소표시%K-SVD%용여자전%마씨거리
hull detection%sparse representation classification%K-SVD%over-complete dictionary%mahalanobis distance
为进一步强化航道安全，解决海事CCTV人工值守、非自动化问题，提出了基于稀疏表示的船体检测方法。利用稀疏表示实现对船体的检测时，首先构建样本特征矩阵，然后利用K-SVD算法对样本特征矩阵进行学习，得到冗余字典，最后对测试样本进行重构，根据马氏距离判断测试样本属性。通过与传统方法的试验比较，实验结果表明，该算法实时性好、检测准确率高，可以很好地对CCTV视频监控的船体进行检测与跟踪，解决CCTV人工值守、非自动化问题，节省大量人力资源。
為進一步彊化航道安全，解決海事CCTV人工值守、非自動化問題，提齣瞭基于稀疏錶示的船體檢測方法。利用稀疏錶示實現對船體的檢測時，首先構建樣本特徵矩陣，然後利用K-SVD算法對樣本特徵矩陣進行學習，得到冗餘字典，最後對測試樣本進行重構，根據馬氏距離判斷測試樣本屬性。通過與傳統方法的試驗比較，實驗結果錶明，該算法實時性好、檢測準確率高，可以很好地對CCTV視頻鑑控的船體進行檢測與跟蹤，解決CCTV人工值守、非自動化問題，節省大量人力資源。
위진일보강화항도안전，해결해사CCTV인공치수、비자동화문제，제출료기우희소표시적선체검측방법。이용희소표시실현대선체적검측시，수선구건양본특정구진，연후이용K-SVD산법대양본특정구진진행학습，득도용여자전，최후대측시양본진행중구，근거마씨거리판단측시양본속성。통과여전통방법적시험비교，실험결과표명，해산법실시성호、검측준학솔고，가이흔호지대CCTV시빈감공적선체진행검측여근종，해결CCTV인공치수、비자동화문제，절성대량인력자원。
In order to enhance securities of water-way and improve the effectiveness of the CCTV system, an approach based on sparse representation is proposed to automatically detect and track the vessels on the water-way. First, the dictionary of the samples is constructed by using the K-SVD algorithm to learn and train the samples' dictionary, and then the over-complete dictionary that can be used to represent the test samples is obtained. Finally, the mahalanobis distance between the test sample and the reconstructed sample is used to classify the test sample. This method is compared with the traditional methods. The experimental results show that the effectiveness of the vessel detection based on SR outperforms the traditional SVM method in the efficiency and the accuracy, which can solve the vessel detection problem.
