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In this paper, we propose a novel approach for SSS registration based on modified phase correlation, which is capable of handling low resolution and noise. The modified phase correlation combines threshold segmentation with phase correlation to carry out side-scan sonar (SSS) image registration. Image registration aims to transform images obtained from different views to the same coordinate. Underwater...
Underwater object detection and segmentation has been attracting a lot of interest, and recently various systems have been designed. In this paper, we introduce a novel technique to automatically detect and segment objects from underwater images via saliency-based region merging. The method is composed of three main steps. Firstly, a salient object detection model is used to detect the position of...
For development of an intelligent unmanned autonomous underwater vehicle (AUV), sensor data needs to be processed online for navigation and mission planning. In this work, we suggest a complete workflow and a processing chain to retrieve multibeam sonar data for AUV control. Our approach is based on the well-known image processing library OpenCV which provides sophisticated image recognition algorithms...
For the first time, the application of the amplitude dominant component analysis (ADCA) to the segmentation of sonar images is explored. We exploit the saliency of the objects in side scans sonar images for underwater mines recognition. Due to the textural and multicomponent nature of the sonar image, a set of bandpass filters is used to decompose the image into narrowband components which lends itself...
Computer vision has become the tool of two-dimensional image recognition and analysis, which mainly means extracting image features. But the problem of robustness and real-time property in complex scenarios makes feature extraction become a challenging task. Visual attention is an important psychological adjustment mechanism in the process of human visual information management, under the guidance...
Phytoplankton are photosynthesizing microscopic organisms that inhabit the upper sunlit layer of almost all oceans and bodies of fresh water. Its abundance and taxonomic composition have impact on marine ecosystem dynamic and global environment change. Therefore, many researchers pay attention to effectively monitoring phytoplankton quantity and species composition. In order to realize this purpose,...
This paper presents the bio-inspired underwater 3D SLAM algorithm called DolphinSLAM. First, every module of the DolphinSLAM algorithm is explained. Then, the effects of parameter variations regarding the parameters of the DolphinSLAM algorithm are investigated based on the use of the Underwater Simulator (UWSim). The parameters of interest are i) the image feature extractors, ii) the vocabulary size...
Daily increasing underwater visual data makes automatic object detection and recognition a great demand and challenging task. In this paper, we adopt a region proposal network to accelerate underwater object detection and recognition from Faster R-CNN. This process implement detection acceleration by using convolutional networks to generate high-quality object candidates, and by sharing these networks...
Zooplankton are the key components of marine food webs. The abundance of it influences the ocean ecological balance. To efficiently monitor species richness of zooplankton and protect marine environment, marine biologists and computer vision experts started to research automated zooplankton classification system with computer vision technologies. Most current research focuses on achieving high classification...
One of the main recent research trends of the Italian Interuniversity Research Center on Integrated Systems for Marine Environment (ISME) is the use of marine cooperative teams of autonomous robots within the fields of security, prevention and management of emergencies at sea. Such fields are of worldwide interest for obvious reasons, but they have recently gained relevance in the current historical...
In this paper, we try to combine Bag-of-Words (BoW) with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) together for one kind of sparse representation in the seafloor visual saliency evaluation. Properties in the water, due to the large amount of acoustic noises, sonar signals are easily polluted and interfered during image collection, and the sonar images usually diverge from...
Zooplankton are quite significant to the ocean ecosystem for stabilizing balance of the ecosystem and keeping the earth running normally. Considering the significance of zooplantkon, research about zooplankton has caught more and more attentions. And zooplankton recognition has shown great potential for science studies and mearsuring applications. However, manual recognition on zooplankton is labour-intensive...
Coral reefs exhibit the highest biodiversity in the ocean and are an extremely vulnerable ecosystem. Monitoring the state of the reefs is a tedious process performed by human divers which can be automated. This paper presents the use of several inexpensive drifting sensor nodes in order to reconstruct a visual mosaic of a shallow coral reef. The drifters produce geo-referenced visual data from a downward...
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