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The long term goal of artificial intelligence and computer vision is to be able to build models of the world automatically and to use them for interpretation of new situations. It is natural that such models are efficiently organized in a hierarchical manner; a model is build by sub-models, these sub-models are again build of another models, and so on. These building blocks are usually shareable;...
We consider the problem of comparing deformable 3D objects represented by graphs, i.e., Triangular tessellations. We propose a new algorithm to measure the distance between triangular tessellations using a new decomposition of triangular tessellations into triangle-Stars. The proposed algorithm assures a minimum number of disjoint triangle-Stars, offers a better measure by covering a larger neighborhood...
This paper describes an multi-features indexing system for use in Content Based Image Retrieval. The standard CBIR approach is simple and usually use a single information such as shape, scale or color, which leads to recognition problems in some cases, to remedy this problematic, we use additional features to combine types of information. From many points of view local descriptors are relatively different,...
Load profiles are a crucial tool for power system planning and operation, and also in several operations of electricity markets. This article proposes a new methodology for the determination of load profiles based on a two-step approach. The first phase employs a neural network autoencoder to reduce the dimensionality of the input vectors. The second phase is a clustering process based on the Kohonen...
Oil exploration mainly targets to the locations that are closed or below the salt bodies, in the underlying geologic structure. With time the computational tools which can help in interpreting, analysing and estimating the geometry with its position has been increased. But still at many time the data which is gathered using these computational tools is recognized with the lack of resolution and poor...
Finding a method which allows a computer recognition to be close to human recognition is a goal of many works in the present. We have set this goal too. According to us, we need to find function for simple recognition of shapes in the images as first step of this goal. Result of this method provides input of our system of recognition. System form depends on the result of shape recognition method....
We present a novel real time 3D Automatic Target Recognition algorithm appropriate for LIDAR based time critical applications. Its main contribution is the Constant False Alarm Rate adaptive threshold combined with the Projection Density Energy and the transformation of the 3D problem into multiple 2Ds. Our approach is invariant to 3D rotations combined with scale change, Gaussian noise and uniform...
Trademark retrieval (TR) is the problem of retrieving similar trademarks (logos) for a query, and the main aim is to detect copyright infringements in trademarks. Since there are millions of companies worldwide, automatically retrieving similar trademarks has become an important problem, and currently, checking trademark infringements is mostly performed manually by humans. However, although there...
This paper presents an application of 3d-reconstruction and graph theory in the field of archaeology. The classification and reconstruction of ancient pots and vessels out of fragments (so-called sherds) is an important aspect of archaeological research work. Up to now this is a time consuming, inaccurate, and subjective task which leads to tons of unclassified fragments in archives. Computer aided...
Archival of images in databases, enabling further study with respect to their contents, is at our focus of attention. The major difficulties are i) the processing of a large number of images, ii) that the steadily growing number of images increase the complexity of the pattern recognition problems to be solved. We propose orientation radiograms, to be used as image signatures for shape based queries...
The automatic recognition of planes in aerial images is an important application in the image analysis field. However, it remains a problem despite many years of work due to the arbitrary original poses and the variation in the shapes of planes. This paper proposes a novel approach for automatic aircraft detection based on statistical theory and common features of different kinds of planes. Experiments...
In this paper we investigate performance metrics for quantitative evaluation of object-based video segmentation algorithms. The metrics address the case when ground-truth video object planes are available. The proposed metrics are used to evaluate three essentially different approaches for video segmentation, i.e., an edge-based [1], a motion clustering based [2], and a total feature vector clustering...
An experimental analysis of two-dimensional (2D) shape classification method based on moment invariants is presented. Various types of translation, scale and rotation invariants are used to construct feature vectors for classification. The performance is evaluated using five different objects picked up from real scenes with a TV camera. Silhouettes and contours are extracted from nonoccluded 2D objects...
Growth of the image mining arena calls for the need of quality image retrieval techniques in par with the human perception which are invariant to scale and rotation. An optimized content based image retrieval system based on local visual attention features to bridge the semantic gap problem is proposed. The approach involves the salient point detection using Scale Up Robust Features (SURF) detector...
The connected load of consumers is known to the distribution utility but the usage pattern of them is not known without smart meters installed on the site. Furthermore, constituents of the feeders at primary distribution level are also unknown. In partially deregulated developing countries implementation of Time of Use tariff becomes a challenging task. This paper addresses this crucial issue where...
This study presents a method for detecting an object by using several features. Features are extracted based on the statistical distribution of points on the bitmap image of the shape. It detect the shape of an image by using geometrical features and then select the clustered of image that matched that shape from a large database. In this approach the image of object are divided into zones and find...
Currency recognition system is one of the fast growing research fields under image processing. This paper proposes a novel method for Indian currency recognition. Our proposed approach identifies denomination by extracting features like Center Numeral, Shape, RBI Seal, Latent Image and Micro Letter. Principal Component Analysis is used to reduce the dimensions and a similarity based classifier is...
In this paper, we propose a normalized cone histogram features method to recognize human actions in video clips. The cone features are extracted based not on the center of gravity as is common, but on the head position of the extracted human region. Initially, the head, hands and legs positions are determined. Thereafter, the distances and orientations between the head and the hands and legs are the...
Biomedical research in last decade or so has seen the development of highly accurate algorithms focused on the detection and classification of the brain tumor into malignant or benign. As a result of these advancements a new research direction has emerged which focuses on categorizing the brain tumors based on their types, such as Glioma, Metastases, and Meningioma etc. In this paper, we present a...
Regarding the palms recognition system studies, despite achieving a high success rate, hygiene problems in systems with contact and problems arising from changes in the alignment of the hand pose in non-contact ones have been encountered. To resolve these problems, 3D palmprint recognition systems have been developed, however these systems have not had the opportunity to spread due to expensive technologies...
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