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In this paper, a novel logo recognition algorithm based on a set of invariant features, which are calculated by using Radon transform and complex moments is proposed. This set of features is invariant to Rotation, Scaling, and Translation (RST) and it is also robust to additive noise. Radon transform is powerful tool for rotation, scaling, and translation properties which make it useful for our purpose...
Human activity recognition is one of the most intensively studied areas of computer vision and pattern recognition in recent years. A wide variety of approaches have shown to work well against challenging image variations such as appearance, pose and illumination. However, the problem of low video quality remains an unexplored and challenging issue in real-world applications. In this paper, we investigate...
Motivated by the increased consideration of probability distributions as local descriptors of shape, we propose a local descriptor based on a bivariate circular distribution. Although some bivariate circular distributions are difficult to compute, our descriptor is computationally feasible because it is a generalization of the mixture of von Mises distributions. Using various shapes formed by line...
In this paper an extraction of intensity variance and size-intensity mean features is considered. Their effectiveness is compared for texture image searching.
User interfaces (UIs) are advancing in every direction. The usage of touch screen devices and adaptation their UIs lives its boom. However integrated development environments (IDEs) that are used to develop the same UIs are oversleeping the time. They are directed to developing usable software, but forgot to be usable by themselves. Our goal is to design a new way of user interaction for common IDEs...
Nowadays the effective and fast detection of fruit defects is one of the main concerns for fruit selling companies. This paper presents a new approach that classifies fruit surface defects in color and texture using Radial Basis Probabilistic Neural Networks (RBPNN). The texture and gray features of defect area are extracted by computing a gray level co-occurrence matrix and then defect areas are...
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...
The analysis of 2D flow data is often guided by the search for characteristic structures with semantic meaning. One way to approach this question is to identify structures of interest by a human observer, with the goal of finding similar structures in the same or other datasets. The major challenges related to this task are to specify the notion of similarity and define respective pattern descriptors...
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...
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