In this paper, a 532nm laser polarization underwater target detection information processing system is designed. Firstly, combined with GPS detection, the polarization characteristic data and location information of the underwater target are obtained by laser polarization technique. Then the polarization characteristic database is established on the basis of existing polarization characteristic data. Analyze and compare the measured polarization data with the existing polarization characteristic data so as to quickly complete the target identification and classification. Finally, use the acquired location and classification information to reconstruct three-dimensional model of the measured terrain and restore underwater scene vividly. The research of this subject is of great significance for the marine resources development, underwater engineering monitoring, submarine environmental monitoring and so on.
In this paper, a novel target detection and tracking algorithm based on visual attention is proposed. Firstly, the algorithm extracts saliency map of the first frame by improved visual attention algorithm, then detects targets which moving very slowly or even close to stationary after eliminating the interference of background factors. Secondly, it makes the mean shift algorithm’s kernel fixed bandwidth to be a dynamically changing bandwidth, so it not only retains the feature of traditional mean shift algorithm and can accomplish real-time tracking, but also can reduce background interference. Thirdly, the target model is established based on the saliency map, so the model is described by a variety of features. Therefore, when the target’s single feature changes, as size or shape, it still can detect the target. Lastly, it uses the modified meanshift algorithm to track moving targets, which can reduce the probability of losing target. Experimental results show that this algorithm is applicable to image sequences of both infrared and visible light, and it has good tracking performance. What’s more, the algorithm provides the motion information of the moving targets, so it gives a possibility for accurate positioning.
The detection of foreign substances in transparent-bottled liquid is a key procedure in production. An improved algorithm based on the combination of guided filter and visual background extractor (ViBe) is proposed for the detection of foreign substances in transparent-bottled turbid liquid on the market. In the stage of image preprocessing, the image enhancement is carried out by the guided filter and then the liquid region is detected by the Hough transform. Finally, the area of the connected region is determined for the image processed by the ViBe algorithm to remove the tiny noise in detection images. The simulation results show that the proposed algorithm can not only detect foreign substances in transparent liquid but also detect foreign substances in the turbid liquid.