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In this paper, we present a one dimensional descriptor for the two dimensional object silhouettes associated with each level of barycenter contour for multiple views shape matching and retrieval. Firstly, the barycenter contour is applied onto the shape contour. Then the averaging multi-triangle area representation (AMTAR) at each level of barycenter contour is computed as the shape descriptor. Finally,...
In this paper we have developed a connectivity based cluster validity index. This validity index is able to detect the number of clusters automatically from data sets having well separated clusters of any shape, size or convexity. The proposed cluster validity index, connect-index, uses the concept of relative neighborhood graph for measuring the amount of "connectedness" of a particular...
We propose and describe our implementation of an automatic control system for the center wavelength of a fiber Bragg grating. The proposed system consists of a Fabry-Perot filter and cantilever structure controlled by a step motor interfacing computer. We considered the change of the center wavelength and the reflective spectrum shape for a given FBG according to the translation distance of the push...
Level set method (LSM) is the efficient computation method for the interface capturing with corresponding of advection equation attend topological change of interface. LSM is consisted of the generation of signed distance function from initial interface and the convergence computation of the interface evolution for the target shape using the advection equation in conjunction with the mean curvature...
A novel efficient skeleton extraction algorithm is proposed, which is based on feature points extraction and Reeb graph theories. Because of the topological facility of feature points, a model can be divided into several branches according to them. One feature point can present one branch. So we just extract the other point of the branch - that could be skeleton point, connect these points with their...
An interesting challenge in image processing is to classify shapes of polygons formed by selecting and ordering points in a 2D cluttered point cloud. This kind of data can result, for example, from a simple preprocessing of images containing objects with prominent boundaries. Taking an analysis-by-synthesis approach, we simulate high-probability configurations of sampled contours using models learnt...
The method of the shadow detection and remove which has application value is proposed based on analyzing visual surveillance purposes. The method proposed is essentially based on linear ratio and shadow direction angle threshold to locate the rough shadow regions, considering the relationship of the probability whether it is a shadow pixels and distances which between the shadow pixels and the centroids...
This paper provides a novel content-based image retrieval algorithm based on ROI (Region Of Interest) by using SIFT (Scale Invariant Feature Transform) feature matching. SIFT descriptors, which are invariant to image scaling and transformation and rotation, and partially invariant to illumination changes and affine, present the local features of an image. Therefore, feature keypoints can be extracted...
Clustering is the problem of partitioning a (large) set of data using unsupervised techniques.Today, there exist many clustering techniques. The most important characteristic of a clustering technique is the shape of the cluster it can find. In this paper, we propose a method that is capable to find arbitrary shaped clusters and uses simple geometric constructs, Circlusters. Circlusters are different...
This paper describes a novel method for extracting fingerprints of executables. A new data visual approach based on data field is imported. The 3-tuple (in-degree, out-degree, function call relationship) extracted from call graph are used for constructing data field and the potential field graph. This potential field graph is fingerprinted by the method of shape invariant moments which is mature and...
This paper proposes an angular invariant feature for registration procedure to perform reliable matching between a given model shape and a data shape. The feature is defined by a k-dimensional vector with k angles between the normal vector of each point and its k-nearest-neighbors individually. The feature is invariant to scale transformation, rotation transformation. Particularly, when we register...
Clustering is one of the fundamental data mining tasks. Many different clustering paradigms have been developed over the years, which include partitional, hierarchical, mixture model based, density-based, spectral, subspace, and so on. The focus of this paper is on full-dimensional, arbitrary shaped clusters. Existing methods for this problem suffer either in terms of the memory or time complexity...
We propose that appearance descriptors derived from the complete animacy of an object during its scene presence more comprehensively capture the essence of an object than descriptors that merely encode uncorrelated sets of its instantaneous appearances. During its frame presence, an object presents itself in many poses with differing frequencies, thus generating multiple modes of varying strengths...
In this paper, we propose two new affine invariant shape descriptors, the ICA-Fourier descriptor and the PCA-Fourier descriptor. We tested the descriptors by using them as features for shape based silhouette image retrieval. Experiments on a 1000 silhouette image database show promising retrieval rates of 95.41% and 93.63%, using the ICA-Fourier descriptor and the PCA-Fourier descriptor, respectively...
Several validity indices have been designed to evaluate solutions obtained by clustering algorithms. Traditional indices are generally designed to evaluate center-based clustering, where clusters are assumed to be of globular shapes with defined centers or representatives. Therefore they are not suitable to evaluate clusters of arbitrary shapes and densities, where clusters have no defined centers...
In recent years, the demand for a content-based 3D model retrieval system becomes an important issue. In this study, a novel feature, derivative elevation descriptor (DED), is proposed to extract the exterior information of 3D model. The derivative elevation descriptor (DED) is combined with the elevation descriptor (ED) to retrieval 3D models based on the exterior shape information. Moreover, to...
As a new theory for studying non-linear complex systems, fractal geometry has received much attention recently. Based on the relationship between length of curve and change of scale as well as the idea that a closed curve is formed by a certain amount of unclosed curves, we present an improved Douglas-Peuker method (IDPM) based algorithm. Our algorithm can not only keep the shape and details of the...
Current approaches to organising units in strategic video games are typically implemented via static formations. Static formations are not capable of adapting effectively to opponent tactics. In this paper we discuss an approach to organising units by learning the effectiveness of a formation in actual play, and directly applying learned formations according to the classification of the opponent player...
Cluster analysis is a data mining approach for unsupervised learning. However, the use of clustering as a data mining tool has been a cause of growing concern as the use of this technology is violating individual privacy. This paper presents a method for privacy preserving clustering through cluster bulging. In this method, the objects of the database are first aligned into clusters based on a similarity...
Multidimensional arrays storing multidimensional data in MOLAP are usually very sparse. They also suffer from the problem that the time consumed in sequential access to array elements heavily depends on the dimension along which the elements are accessed. This problem of ldquodimension dependencyrdquo would be alleviated by dividing the whole array into the set of smaller hypercube shaped subarrays...
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