Surface ship target detection based on Gaussian mixture model
In complex sea environments,the detection of ship targets on the sea surface becomes a technological chal-lenge due to factors such as irregular changes in sea waves,shore islands,and ship shadows.To address this issue,a Gaussi-an mixture model based method for ship target detection on the sea surface is proposed.Combining multi-scale median filter-ing and Canny edge detection processing to collect sea surface ship images and obtain edge images,the Hough transform is used to extract candidate lines from the edge image,and the length and color features are integrated to accurately extract sea antennas from the candidate lines.The background compensation of the ship image is completed,and a Gaussian mixture model is established based on the background compensated image.Through model initialization Correction,background measurement,and foreground segmentation are used to detect ship targets,and combined with Hotelling orthogonal trans-formation to suppress ship target shadows,completing image post-processing.The experimental results show that the image clarity is best when the scale of median filtering is 2.This method can effectively extract sea antennas,complete background compensation for ship images,and accurately detect ship targets on the sea.Combining shadow suppression can improve the accuracy of ship target detection and meet the needs of ship target detection on the sea.
Gaussian mixture modelmulti-scale median filteringCanny edge detectionHough transformationHotelling transformationshadow suppression
万方数据
维普
