Search results for " algorithm"
showing 10 items of 2538 documents
Introducing Pseudo-Singularity Points for Efficient Fingerprints Classification and Recognition
2010
Fingerprint classification and matching are two key issues in automatic fingerprint recognition. Generally, fingerprint recognition is based on a set of relevant local characteristics, such as ridge ending and bifurcation (minutiae). Fingerprint classification is based on fingerprint global features, such as core and delta singularity points. Unfortunately, singularity points are not always present in a fingerprint image: the acquisition process is not ideal, so that the fingerprint is broken, or the fingerprint belongs to the arch class. In the above cases, pseudo-singularity-points will be detected and extracted to make possible fingerprint classification and matching. As result, fingerpr…
Video Indexing Using MPEG Motion Compensation Vectors
2003
In the last years a lot of work has been done on color, textural, structural and semantic indexing of "content-based" video databases. Motion-based video indexing has been less explored, with approaches generally based on the analysis of optical flows. Compressed videos require the decompression of the sequences and the computation of optical flows, two steps computationally heavy. In this paper we propose some methods to index videos by motion features (mainly related to camera motion) and by motion-based spatial segmentation of frames, in a fully automatic way. Our idea is to use MPEG motion vectors as an alternative to optical flows. Their extraction is very simple and fast; it doesn't r…
Video indexing using optical flow field
2002
The increasing development of advanced multimedia applications requires new technologies for organizing and retrieving by content databases of digital video. Several content based features (color, texture, motion, etc.) are needed to perform a reliable content based retrieval. We present a method for automatic motion based video indexing and retrieval. A prototypal system has been developed to prove the validity of our approach. Our system automatically splits a video into a sequence of shots, extracts a few representative frames (said r-frames) from each shot and computes some motion based features related to the optical flow field. Motion based queries are then performed either in a quali…
Pedestrian Tracking in 360 Video by Virtual PTZ Cameras
2018
Since the data acquired by a PTZ camera change while adjusting the pan, tilt and zoom parameters, the results of tracking algorithms are difficult to reproduce; such diffi- culty limits the development and the comparison of tracking algorithms with PTZ cameras. The recently introduced 360- degree cameras acquire spherical views of the environment, generally stored as equirectangular images. Each pixel of an equirectangular image corresponds to a point on the spherical surface. A gnomonic projection can be used to project the points on the spherical surface onto a plane tangent to the sphere. Such tangent plane can be interpreted as the image plane of a virtual PTZ camera oriented towards th…
Morphological exponential entropy driven-HUM.
2006
This paper presents an improvement to the Ex- ponential Entropy Driven - Homomorphic Unsharp Masking (E 2 D − HUM ) algorithm devoted to illumination artifact sup- pression on Magnetic Resonance Images. E 2 D−HUM requires a segmentation step to remove dark regions in the foreground whose intensity is comparable with background, because strong edges produce streak artifacts on the tissues. This new version of the algorithm keeps the same good properties of E 2 D − HUM without a segmentation phase, whose parameters should be chosen in relation to the image. I. INTRODUCTION Most of the studies on illumination correction found in literature are oriented to brain (18) magnetic resonance images (…
A distributed Bayesian approach to fault detection in sensor networks
2012
Sensor networks are widely used in industrial and academic applications as the pervasive sensing module of an intelligent system. Sensor nodes may occasionally produce incorrect measurements due to battery depletion, dust on the sensor, manumissions and other causes. The aim of this paper is to develop a distributed Bayesian fault detection algorithm that classifies measurements coming from the network as corrupted or not. The computational complexity is polynomial so the algorithm scales well with the size of the network. We tested the approach on a synthetic dataset and obtained significant results in terms of correctly labeled measurements.
QoS-Aware Fault Detection in Wireless Sensor Networks
2013
Wireless sensor networks (WSNs) are a fundamental building block of many pervasive applications. Nevertheless the use of such technology raises new challenges regarding the development of reliable and fault-tolerant systems. One of the most critical issues is the detection of corrupted readings amidst the huge amount of gathered sensory data. Indeed, such readings could significantly affect the quality of service (QoS) of the WSN, and thus it is highly desirable to automatically discard them. This issue is usually addressed through “fault detection” algorithms that classify readings by exploiting temporal and spatial correlations. Generally, these algorithms do not take into account QoS re…
Resilient hexapod robot
2017
In this paper, we present a method of learning desired behaviour of the specific robotic system and transfer of the existing knowledge in the event of partial system failure. Six-legged robot (hexapod) built on top of the Bioloid platform is used for the method verification. We use genetic algorithms to optimize the hexapod's gait, after which we simulate physical damage caused to the robot. The goal of this method is to optimize the gait in accordance with the actual robot morphology, instead of the assumed one. Also, knowledge that was previously gained will be transferred in order to improve the results. Nonstandard genetic algorithm with the specific mixed population is used for this.
3D Map Computation from Historical Stereo Photographs of Florence
2018
The analysis of early photographic sources is fundamental for documenting and understanding the evolution of a city so rich in history and art as Florence. Indeed, by the 1860s several photographers used to work in town, and their images (often obtained through stereoscopic set-ups) can help us to reconstruct Florence in 3D as it was by the time of the Italian unification. The first and most delicate part of such reconstruction process is the computation of disparity maps from the historical stereo pairs. This is a very challenging task for fully-automatic computer vision algorithms, since XIX century photographs are affected by several problems—ranging from superficial damages to asynchron…
Image Segmentation through a Hierarchy of Minimum Spanning Trees
2012
Many approaches have been adopted to solve the problem of image segmentation. Among them a noticeable part is based on graph theory casting the pixels as nodes in a graph. This paper proposes an algorithm to select clusters in the images (corresponding to relevant segments in the image) corresponding to the areas induced in the images through the search of the Minimum Spanning Tree (MST). In particular is is based on a clustering algorithm that extracts clusters computing a hierarchy of Minimum Spanning Trees. The main drawback of this previous algorithm is that the dimension of the cluster is not predictable and a relevant portion of found clusters can be composed by micro-clusters that ar…