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An approach for an efficient clustering of 3D line segments based on an unsupervised competitive neural network is applied to a set of high resolution satellite image data in this paper. The unsupervised competitive neural network, called centroid neural network for clustering 3D line segments (CNN-3D), utilizes the characteristics of 3D line segments. Successful application of CNN-3D can lead accurate...
Video-based moving vehicle detection and tracking are important parts of modern intelligent transportation system (ITS). They can provide valuable information such as vehicle velocity and trajectory for ITS. However, vehicle tracking at urban intersection is more challenging than that at highway, due to the complicated scenarios, such as the variety of vehicle moving direction, inter-vehicle clustering...
This paper presented a video moving object segmentation and tracking system based on the active contour and the color classification models. First, the active contour model is applied to segment the target object in the initial frame. From the segmented object, the object and background regions are extracted. Then the object and the background regions are separately clustered according to color feature...
This paper presents a fast and reliable approach for detecting 3D line segment from 3D point clouds. The main idea is to discover weak matching of line segments by re-projecting 3D point to 2D image plane and infer 3D line segment by spatial constraints. On the basis of 2D Line Segment Detector (LSD) and multi-view stereo, the proposed algorithm firstly re-projects the spatial point clouds into planar...
In this paper, we present a graph cut application dealing with MRI brain image segmentation. We here propose another emerging approach of region segmentation based on graph cut which supports on the eigenspace characteristics and the perceptual grouping properties to classify brain tumoral tissue. Image segmentation is considered as solving the partitioning clustering problem by extracting the global...
In the paper, we formulate a new energy function followed by the use of graph cuts to refine the disparity map which takes segment as node. Firstly, the robust disparity plane fitting is modeled and the method of Singular Value Decomposition (SVD) is used to solve least square. In order to ensure reliable pixel sets for the segment, we filter out outliers through three main rules, namely; cross-checking,...
Traditional iris recognition systems can achieve excellent performance in both verification and identification. However, most of the existing systems adopted a similar technique to deal with the iris image. In this paper, we propose a novel matching strategy with invariant properties, which is based on the possibilistic fuzzy clustering algorithm, to compare a pair of local feature sets. Moreover,...
In this paper we propose a novel method for object tracking in video images. The method is based on image segmentation and pattern matching. All moving and still objects in video images can be detected accurately with the help of efficient image segmentation techniques. We propose a hybrid algorithm for image segmentation using the notion of Particle Swarm Optimization (PSO) and Fuzzy-C-Means (FCM)...
Most existing object-based image retrieval systems are based on single object matching, with its main limitation being that one individual image region (object) can hardly represent the user's retrieval target especially when more than one object of interest is involved in the retrieval. In this paper, we present a Feedback-based Image Clustering and Retrieval Framework (FIRM) using a novel image...
This paper presents an implementation of detecting and recognizing typical obstacles with laser range finders. Mounting the laser range finder with a pitch angle on top of the robot, we can obtain the height information of the obstacle. Techniques, such as clustering, line segment extraction, coordinate transformation, line segment matching, are then applied on the scan data analyzing to detect and...
Methods developed for image annotation usually make use of region clustering algorithms. Visual codebooks are generated from the region clusters of low level features. These codebooks are then, matched with the words of the text document related to the image, in various ways. In this paper, we supervise the clustering process by using three types of side information. The first one is the topic probability...
We present a novel variant of the RANSAC algorithm that is much more efficient, in particular when dealing with problems with low inlier ratios. Our algorithm assumes that there exists some grouping in the data, based on which we introduce a new binomial mixture model rather than the simple binomial model as used in RANSAC. We prove that in the new model it is more efficient to sample data from a...
This paper presents a approach of SIFT feature points matching for image mosaic. This method combines improved K-means clustering and simulated annealing algorithm to match SIFT feature points. Firstly, high robust points are extracted by SIFT algorithm; Secondly, cluster with the initial centers obtained by density function, and then optimize the results of clustering which are used as initial results...
As an important step in an automatic fingerprint recognition system, fingerprint segmentation aims to extract the foreground of a fingerprint image in an efficient way. In this paper, an initiative algorithm for fingerprint segmentation is presented. First, the model of Pulse Coupled Neural Networks (PCNN) is utilized to binarize the fingerprint image. Then, morphological methods are adopted to obtain...
We present an algorithm for clustering sets of detected interest points into groups that correspond to visually distinct structure. Through the use of a suitable colour and texture representation, our clustering method is able to identify keypoints that belong to separate objects or background regions. These clusters are then used to constrain the matching of keypoints over pairs of images, resulting...
Poyang lake of Jiangxi province, China, is the biggest wetland of China. It is one of the largest bases of the migrant birds especially in winter. The nature ecosystem of the region has relationship with the birds' activities, and vice versa. Research of the birds is one of the important ways for knowing the ecosystem. We attempt to set up a system of surveillance and estimation of the bird types...
Several general-purpose algorithms and techniques have been developed for image segmentation. Since there is no general solution to the image segmentation problem, these techniques often have to be combined with domain knowledge in order to effectively solve an image segmentation problem for a problem domain. This paper presents a comparative study of the basic image segmentation techniques i.e. edge-based,...
In this paper, we present a system for pedestrian detection involving scenes captured by mobile bus surveillance cameras in busy city streets. Our approach integrates scene localization, foreground and background separation, and pedestrian detection modules into a unified detection framework. The scene localization module performs a two stage clustering of the video data. In the first stage, SIFT...
In this paper, a novel method is proposed to detect faces based on PCNN time signature and skin color segmentation, in which no training is needed. A test image is first divided into overlapped blocks and extracted PCNN time signature as the detection features, which a two-dimensional image is projected to a one-dimensional feature space. The test blocks are matched to a face template, which can be...
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