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Visual cues like texture, color and context make objects appear distinct from the surroundings, even without gradients between regions. Texture-rich objects are often difficult to segment because algorithms need advanced features which are unique for the image. In this paper we suggest a method for image segmentation that operates without training data. Our method is based on a probabilistic dictionary...
The overall method used for determining disparity in a stereo setup is a widely recognized framework consisting of four steps of cost space computation, cost aggregation, disparity selection, and post-processing. In this paper a cost aggregation approach for a typical local disparity estimation method is introduced. The method introduced is built on top of an existing method called Adaptive Support-Weight...
With the development of computer-aided education and digital library, there have emerged large numbers of digital documents online for education purposes. However, it is far from convenient to retrieve mathematic geometry questions because current retrieval systems largely rely on keywords instead of geometry figure images. We focus on plane geometry figure (PGF) image retrieval aiming at retrieving...
Full understanding of the architecture of the brain is a long term goal of neuroscience. To achieve it, advanced image processing tools are required, that automate the the analysis and reconstruction of brain structures. Synapses and mitochondria are two prominent structures with neurological interest for which various automated image segmentation approaches have been recently proposed. In this work...
With this paper, we present an algorithm for the anti-aliased Euclidean distance transform, based on wave front propagation, that can easily be extended to images of arbitrary dimensionality and sampling lattices. We investigate the behavior and weaknesses of the algorithm, applied to synthetic two-dimensional area-sampled images, and suggest an enhancement to the original method, with complexity...
In emerging 3D video coding, depth has significant importance in view synthesis, scene analysis, and 3D object reconstruction. Depth images can be characterized by sharp edges and smooth large regions. Most of the existing depth coding techniques use intra-coding mode and try to preserve edges explicitly with approximated edge modelling. However, edges can be implicitly preserved as long as the transformation...
The timely and accurate identification of plant species is a persistent challenge as pressure from human activity threatens global flora biodiversity. Most existing research on computer based plant species identification has focused on using leaf contour, signature and spectral analysis techniques alongside textural properties of the leaf lamina. However, these global feature based methods often suffer...
This paper proposes to extend the conventional discrete Fourier transform (DFT) descriptor to discrete fractional Fourier transform (DFrFT) descriptors for representing edges in images. The DFrFT descriptors of training images are employed for constructing a dictionary. However, it is required to determine the optimal rotational angles. This problem is formulated as an optimization problem such that...
With the explosion of social media on the Web, significant efforts have been dedicated to the research on social image retrieval and ranking. However, most existing social image ranking methods are disturbed by noisy tags which brings a strong need to find some complementary information for image ranking. Thanks to the rapid development of mobile devices, online social images increasingly attached...
This paper presents a system for automatically classifying the resting location of a moving object in an indoor environment. The system uses an unsupervised neural network (Self Organising Feature Map) fully implemented on a low-cost, low-power automated home-based surveillance system, capable of monitoring activity level of elders living alone independently. The proposed system runs on an embedded...
This paper proposes a pulse coupled neural network with multi-channel (MPCNN) linking and feeding fields for multispectral image processing. Different from the conventional PCNN, pulse based RBF units are introduced into the model neurons of PCNN to determine the fast links among neurons with respect to their spectral feature vectors and spatial proximity. This MPCNN can be implemented in parallel...
Semi-automatic/automatic road extraction from remote sensing imagery is one of the hot topics in the field of remote sensing, surveying and mapping and computer vision, etc. Traditional methods based on Marr's Computation Theory of Vision follow the pattern of local-to-global features extraction. However, in high resolution image, the local features such as road boundary and road width are easily...
In this paper we propose and evaluate a new technique that localizes the description ability of the well established MPEG-7 and MPEG-7-like global descriptors. We employ the SURF detector to define salient image patches of blob-like textures and use the MPEG-7 Scalable Color (SC), Color Layout (CL) and Edge Histogram (EH) descriptors and the global MPEG-7-like Color and Edge Directivity Descriptor...
This paper addresses the problem of image annotation using a combination of visual and semantic information. Our model involves two stages: a Nearest Neighbor computation and a tag transfer stage that collects the final annotations. For the latter stage, several algorithms have been implemented in the past using labels' information or including implicitly some visual features. In this paper we propose...
A method is proposed for fully restoring local image structures of an unknown continuous-tone patch from an input halftoned patch with homogenously distributed dot patterns, based on locally learned dictionary pairs via feature clustering. Experimental results show that the use of the paired dictionary selected by the local edge orientation enables the restored continuous-tone images to include well-expressed...
This paper presents a defocus-invariant image registration method for measuring the shifting value between two differently located patterns in an imaging sensor. Existing registration methods fail with unfocused images since features or regions of interest are degraded by defocus. In order to solve this problem, the proposed method consists of three stages: i) pre-generation of the set of point spread...
An effective PSO fuzzy clustering edge detection algorithm is proposed. PSO algorithm and Fuzzy C-Mean algorithm are combined to overcome two shortcomings, namely the initialization sensitivity and the local minimum of standard FCM algorithm in image edge detection. At first, a vector is constructed to describe edge point information, which includes neighborhood homogeneity information measure, orientation...
Rapid growth of visual data processing and analysis applications, such as content based image retrieval, augmented reality, automated inspection and defect detection, medical image understanding, and remote sensing has made the problem of developing accurate and efficient image representation and classification methods one of the key research areas. This research proposes new higher-level perceptual...
Straight line fitting is an important problem in computer and robot vision. We propose a novel method for least squares line fitting that uses both the point coordinates and the local gradient orientation to fit an optimal line by minimizing the proposed algebraic distance. The proposed inclusion of gradient orientation offers several advantages: (a) one data point is sufficient for the line fit,...
In order to optimally control the energy flow in the microgrid, consist of several renewable energy sources, including solar photo electric system and storage system, it is essential to know availability of the specific energy source. So, it is necessary to determine the exact moment of the Sun shading the by clouds as well as shadow duration. These parameters could be obtained by cloud movement tracking...
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