Title :
Object Recognition Algorithm of Sonar Image
Author :
Tian, Xiaodong ; Zhou, Dechao ; Liu, Zhong
Author_Institution :
Inst. of Electron. Eng., Naval Univ. of Eng., Wuhan
Abstract :
In the target detection and recognition of underwater sonar image, object recognition is one of key technologies. With analysis and calculation, three features which have good distinguish degree are chosen to construct feature vector for classification, clustering method, neural network and support vector machine were presented. Correct classification ratio can be above 95%. Simulation result indicates that features presented in this paper have characteristics such as precision and robustness, which reduce dependence of classifying result on classifier
Keywords :
image classification; neural nets; object detection; object recognition; sonar; support vector machines; clustering method; feature vector; image classification; neural network; object recognition algorithm; support vector machine; target detection; underwater sonar image; Clustering algorithms; Clustering methods; Image recognition; Neural networks; Object detection; Object recognition; Sonar detection; Support vector machine classification; Support vector machines; Target recognition;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.345726
