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Side scan sonar (SSS) is a vital sensor for autonomous underwater vehicles (AUVs) to do ocean survey. Many methods have been proposed to carry out SSS image segmentation, among which machine learning algorithms provide outstanding performance. Machine learning algorithms like support vector machine (SVM) and convolutional neural networks (CNN) are the most used. When SVM is used to do pixel-level...
Side-scan sonar image segmentation is an important part in marine surveys, especially when we need to get the topographic features of the seabed. Actually, due to the complexity of the geomorphological characteristics in the seabed, we can't obtain any prior knowledge. Therefore we need an unsupervised system to segment side-scan sonar images automatically. In this paper, a novel segmentation system...
Autonomous Underwater Vehicles (AUVs) are important platform for oceanographic survey. AUVs have been widely applied to many fields, such as the ocean research, oil and gas exploitation, mineral resources investigation, fishing and military. People can obtain important ocean information by segmenting, classifying and recognizing sonar image of AUV. So studying side-scan sonar image is significant...
Multi-targets tracking has shown great prospects in ocean investigations. In this paper, we apply the adaptive background mixture models to extracts the moving target from the image sequences, and propose a new method which is made use of the EKF and SURF-RANSAC to realize multi-targets tracking via multiple underwater cameras. In this method the centroid coordinate homographic mapping and the Speeded...
A new robust lane marking detection algorithm for monocular vision is proposed. It is designed for the urban roads with disturbances and with the weak lane markings. The primary contribution of the paper is that it supplies a robust adaptive method of image segmentation, which employs jointly prior knowledge, statistical information and the special geometrical features of lane markings in the bird's-eye...
Video scene segmentation and classification are fundamental steps for multimedia retrieval, browsing and indexing. In this paper, we present a robust scene segmentation approach based on the Markov Chain Monte Carlo (MCMC) method using the structure of video sequences. In our method, there are two novel approaches to segment video sequences into scenes. The first approach is the use of the video structures...
Recently, bag of words (BoW) model has led to many significant results in visual object classification. However, due to the limited descriptive and discriminative ability of visual words, the resulting performance of visual object classification is still incomparable to its analogy in text domain, i.e. document categorization. Furthermore, for weakly labeled image data, where we only know whether...
An effective approach based on geometric constraint of the motion vector field is proposed to detect camera zoom operation. The approach exploits the valid motion vectors to estimate the center of focus (COF) for zoom, and then calculates the average distance from the COF to valid motion vectors to identify zoom operation. To reduce the influence of object motion, Visual attention mechanism is employed...
Texts in web pages, images and videos contain important clues for information indexing and retrieval. Most existing text extraction methods depend on the language type and text appearance. In this paper, a novel and universal method of image text extraction is proposed. A coarse-to-fine text location method is implemented. Firstly, a multi-scale approach is adopted to locate texts with different font...
In order to protect urethra in radiation therapy of prostate cancer, the urethra must be identified and localized as an organ at risk (OAR) for the inverse treatment planning in intensity modulated radiation therapy (IMRT). Because the prostatic urethra and its surrounding prostate tissue have similar physical characteristics, such as linear attenuation coefficient and density, it is difficult to...
Given a large set of video database, how to connect video segments with a certain set of semantic concepts with least manual labors is an elementary step for video indexing and searching. Due to the large gap between high-level semantics and low-level features, automatic video annotation with high accuracy is a challenging task. In this paper, we propose a novel automatic video annotation framework,...
The document image segmentation is an important component in the document image understanding. kernel-based methods have demonstrated excellent performances in a variety of pattern recognition problems. This paper applies kernel-based methods and Gabor wavelet to the document image segmentation. The feature image are derived from Gabor filtered images. Taking the computational complexity into account,...
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