Multi-layer Architecture For Storing Visual Data Based on WCF and Microsoft SQL Server Database

In this paper we present a novel architecture for storing visual data. Effective storing, browsing and searching collections of images is one of the most important challenges of computer science. The design of architecture for storing such data requires a set of tools and frameworks such as SQL database management systems and service-oriented frameworks. The proposed solution is based on a multi-layer architecture, which allows to replace any component without recompilation of other components. The approach contains five components, i.e. Model, Base Engine, Concrete Engine, CBIR service and Presentation. They were based on two well-known design patterns: Dependency Injection and Inverse of Control. For experimental purposes we implemented the SURF local interest point detector as a feature extractor and $K$-means clustering as indexer. The presented architecture is intended for content-based retrieval systems simulation purposes as well as for real-world CBIR tasks.Comment: Accepted for the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC, June 14-18, 2015, Zakopane, Polan

Public International Law: Environmental Law

Noteworthy international activity relating to the environment occurred in a wide variety of fora in 2000. This chapter provides brief updates on some of the most significant developments. Though by no means a comprehensive review, the chapter reflects the wide sweep of issues and large number of entities now involved in the development of international environmental law, at the start of this new century. It also reflects how critical and complex this international work is, and how much remains to be done

Segmentation and edge detection based on modified ant colony optimization for iris image processing

Ant colony optimization (stocktickerACO) is a meta-heuristic algorithm inspired by food searching behavior of real ants. Recently stocktickerACO has been widely used in digital image processing. When artificial ants move in a discrete habitat like an image, they deposit pheromone in their prior position. Simultaneously, vaporizing of pheromone in each iteration step avoids from falling in the local minima trap. Iris recognition because of its great dependability and non-invasion has various applications. simulation results demonstrate stocktickerACO algorithm can effectively extract the iris texture. Also it is not sensitive to nuisance factors. Moreover, stocktickerACO in this research preserves details of the various synthetic and real images. Performance of ACO in iris segmentation is compared with operation of traditional approaches such as canny, robert, and sobel edge detections. Experimental results reveal high quality and quite promising of stocktickerACO to segment images with irregular and complex structures

Fast FCM with spatial neighborhood information for brain MR image segmentation

Among different segmentation approaches Fuzzy c-Means clustering (FCM) is a welldeveloped algorithm for medical image segmentation. In emergency medical applications quick convergence of FCM is necessary. On the other hand spatial information is seldom exploited in standard FCM; therefore nuisance factors can simply affect it and cause misclassification. This paper aims to introduce a Fast FCM (FFCM) technique by incorporation of spatial neighborhood information which is exploited by a linear function on fuzzy membership. Applying proposed spatial Fast FCM (sFFCM), elapsed time is decreased and neighborhood spatial information is exploited in FFCM. Moreover, iteration numbers by proposed FFCM/sFFCM techniques are decreased efficiently. The FCM/FFCM techniques are examined on both simulated and real MR images. Furthermore, to considerably decrease of convergence time and iterations number, cluster centroids are initialized by an algorithm. Accuracy of the new approach is same as standard FCM. The quantitative assessments of presented FCM/FFCM techniques are evaluated by conventional validity functions. Experimental results demonstrate that sFFCM techniques efficiently handle noise interference and significantly decrease elapsed time

Automatic reduction of wireless capsule endoscopy reviewing time based on factorization analysis

Wireless capsule endoscopy (WCE) is a painless and easy process to screening of the gastrointestinal (GI) tract. During WCE procedure, a huge amount of the endoscopy video frames is generated, however, a limited amount of data is actually useful for diagnosis. Manually reviewing all endoscopy frames is tedious, time-consuming and prone to physician error. In this paper, we propose a novel capsule video summarization framework to reduce WCE reviewing time using the factorization analysis based on sliding window singular value decomposition (SVD). Through the proposed approach, in a quality assessment stage, poor quality frames are removed from the endoscopy video. Adaptive sliding window SVD is then employed to extract the salient video frames. The average recall and precision were estimated by 0.92 and 0.94 for our local database. The quantitative and qualitative results demonstrate that the proposed approach outperforms the existing WCE keyframe extraction methods and provides video keyframes to the gastroenterologists in the clinical applications without discarding significant diagnosis information. © 2020 Elsevier Lt

Bottleneck bichromatic plane matching of points

Given a set of n red points and n blue points in the plane, we are interested to match the red points with the blue points by straight line segments in such a way that the segments do not cross each other and the length of the longest segment is minimized. In general, this problem in NP-hard. We give exact solutions for some special cases of the input point set

On full Steiner trees in unit disk graphs

Given an edge-weighted graph G=(V,E) and a subset R of V, a Steiner tree of G is a tree which spans all the vertices in R. A full Steiner tree is a Steiner tree which has all the vertices of R as its leaves. The full Steiner tree problem is to find a full Steiner tree of G with minimum weight. In this paper we consider the full Steiner tree problem when G is a unit disk graph. We present a 20-approximation algorithm for the full Steiner tree problem in G. As for λ-precise unit disk graphs we present a (10+1λ)-approximation algorithm, where λ is the length of the shortest edge in G

Bottleneck matchings and Hamiltonian cycles in higher-order Gabriel graphs

Given a set P of n points in the plane, the order-k Gabriel graph on P, denoted by k-GG, has an edge between two points p and q if and only if the closed disk with diameter pq contains at most k points of P, excluding p and q. It is known that 10-GG contains a Euclidean bottleneck matching of P, while 8-GG may not contain such a matching. We answer the following question in the affirmative: does 9-GG contain any Euclidean bottleneck matching of P? Thereby, we close the gap for the containment problem of Euclidean bottleneck matchings in Gabriel graphs. It is also known that 10-GG contains a Euclidean bottleneck Hamiltonian cycle of P, while 5-GG may not contain such a cycle. We improve the lower bound and show that 7-GG may not contain any Euclidean bottleneck Hamiltonian cycle of P

Approximating full steiner tree in a unit disk graph

Given an edge-weighted graph G = (V;E) and a sub- set R of V, a Steiner tree of G is a tree which spans all the vertices in R. A full Steiner tree is a Steiner tree which has all the vertices of R as its leaves. The full Steiner tree problem is to find a full Steiner tree of G with minimum weight. In this paper we present a 20-approximation algorithm for the full Steiner tree problem when G is a unit disk graph