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Automated Identification and Analysis of Stationary Targets on Seafloor with Sidescan Sonar Imagery

The normal procedure for the detection of underwater stationary targets is mainly by the application of side-scan sonar. In addition, the identification of targets within the side-scan sonar imagery is primarily based on the visual observation of the operator. Due to its complexity and poor effectiveness, the visual observation procedure was gradually been substituted by numerical analysis procedures and programs. The purpose of the current investigation was dedicated to the development of an automatic image analysis program for the detection and identification of cubic concrete artificial reefs (2 m x 2 m x 2m) in the south-western coastal area off Taiwan.
The major components and methodologies of the program include:
(1)Image acquisition; side-scan sonar at 500 kHz and slant range at 75 m.
(2)Feature extraction; grey level co-occurrence matrix.
(3)Feature Classification; unsupervised Bayesian classifier.
(4)Target identification; cluster analysis.
(5)Target properties analysis, includes circumference, area, central coordinates and quantity of the targets.
Program verification and optimal parameters determination were conducted with a sonograph (650 ¡Ñ 650 pixels) acquired at the Chey-Ding artificial reef site off Kaohsiung County. Feature functions employed in this program include entropy, homogeneity, and mean value. The identification accuracy can reach 93% at the most. In addition, the number of artificial reefs estimated by the program was within 9 to 20, while the actual number is 15.
A realistic evaluation of this program was conducted with a sonograph (2048 ¡Ñ 6050 pixels) acquired at Fang-Liau artificial reef site off Pyngdong County. In addition to the cubic reefs, the targets at this site include cross-shaped artificial reefs with dimensions less than the cubic reefs. The sonograph was divided into smaller blocks with dimensions of 2048 x 550 pixels during evaluation. The results showed that each block can be evaluated based on the value of the seed point obtained by cluster analysis. The seed point which fells between 20.6 and 24.4 indicates that there are cubic reefs existed. Between 15.3 and 17.4 indicates that there are targets with smaller dimensions (i.e., crossed reefs) existed which can not be identified properly. Between 10.1 and 10.9, there is no target existed on the seafloor. The results indicated that the number of targets identified is between 122 and 240.
According to the results of this investigation, the automatic image analysis program can improve the detection and identification of stationary targets within side-scan sonar imagery.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0511108-195144
Date11 May 2008
CreatorsGuo, Meng-wei
Contributorsnone, none, none, Wen-miin Tian, none
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0511108-195144
Rightsoff_campus_withheld, Copyright information available at source archive

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