Search results for "filter"
showing 10 items of 1019 documents
A Semantic Similarity Measure for the SIMS Framework
2008
The amount of currently available digital information grows rapidly. Relevant information is often spread over different information sources. An efficient and flexible framework to allow users to satisfy ef- fectively their information needs is required. The work presented in this paper describes SIMS (Semantic Information Management System), a ref- erence architecture for a framework performing semantic annotation, search and retrieval of information from multiple sources. The work pre- sented in this paper focuses on a specific SIMS module, the SIMS Semantic Content Navigator, proposing an algorithm and the related implementa- tion to calculate a semantic similarity measure inside an OWL …
Noise Filtering Using Edge-Driven Adaptive Anisotropic Diffusion
2008
This paper presents a method aimed to noise removal in MRI (Magnetic Resonance Imaging). We propose an improvement of Perona and Malik's anisotropic diffusion filter. In our schema, the diffusion equation of the filter has been modified to take into account the edges direction, This allows the filter to blur uniform areas, while it better preserves the edges. Both quantitative and qualitative evaluation is presented and the results are compared with other methods.
Optic disc positioning and blood vessels extraction on eye fundus
2009
This paper presents two methods aimed to the optic disc positioning on the retinal images. The first is based on a template of the entire image, while the second is based on the retinal vascularisation. For this second task, also a vessel extraction method is provided. Both the algorithm have been tested on test images of the Drive Database.
Is There Anything New to Say About SIFT Matching?
2020
SIFT is a classical hand-crafted, histogram-based descriptor that has deeply influenced research on image matching for more than a decade. In this paper, a critical review of the aspects that affect SIFT matching performance is carried out, and novel descriptor design strategies are introduced and individually evaluated. These encompass quantization, binarization and hierarchical cascade filtering as means to reduce data storage and increase matching efficiency, with no significant loss of accuracy. An original contextual matching strategy based on a symmetrical variant of the usual nearest-neighbor ratio is discussed as well, that can increase the discriminative power of any descriptor. Th…
Mean shift clustering for personal photo album organization
2008
In this paper we propose a probabilistic approach for the automatic organization of pictures in personal photo album. Images are analyzed in term of faces and low-level visual features of the background. The description of the background is based on RGB color histogram and on Gabor filter energy accounting for texture information. The face descriptor is obtained by projection of detected and rectified faces on a common low dimensional eigenspace. Vectors representing faces and background are clustered in an unsupervised fashion exploiting a mean shift clustering technique. We observed that, given the peculiarity of the domain of personal photo libraries where most of the pictures contain fa…
Exponential Entropy Driven HUM on Knee MR Images
2007
A very important artifact corrupting Magnetic Resonance Images is the RF inhomogeneity. This kind of artifact generates variations of illumination which trouble both direct examination by the doctor and segmentation algorithms. Even if homomorphic filtering approaches have been presented in literature, none of them has developed a measure to determine the cut-off frequency. In this work we present a measure based on information theory with a large experimental setup aimed to demonstrate the validity of our approach.
Job shop scheduling by a parallel approach
1993
The paper deals with a parallel approach to job shop scheduling by a branch and bound methodology using the lower bound proposed by Ashour and Hiremath. The optimal solution is achieved by an iterative-reductive strategy. At each iteration the algorithm investigates the conflict intervals and it selects a subset of the possible solutions. The makespan value, achieved by the parallel processes, gives the upper limit for the admissible lower bound of the intermediate solutions. Furthermore the best makespan reached by each iteration is reused as a filter to reduce the complexity of the next iteration. The computation is speeded up by a parallel implementation, giving the possibility of distri…
Inference of Spatio-Temporal Functions over Graphs via Multi-Kernel Kriged Kalman Filtering
2018
Inference of space-time varying signals on graphs emerges naturally in a plethora of network science related applications. A frequently encountered challenge pertains to reconstructing such dynamic processes, given their values over a subset of vertices and time instants. The present paper develops a graph-aware kernel-based kriged Kalman filter that accounts for the spatio-temporal variations, and offers efficient online reconstruction, even for dynamically evolving network topologies. The kernel-based learning framework bypasses the need for statistical information by capitalizing on the smoothness that graph signals exhibit with respect to the underlying graph. To address the challenge o…
Improving the performance of acousto-optic tunable filters in imaging applications
2010
Acousto-optic tunable filters (AOTFs) can be used as spectral filters for the implementation of multispectral imaging systems. However, obtaining quality images is challenging. In this work, we propose several improvements that enable the use of these systems in quantitative spectroscopic imaging applications. The improvements are based on three pillars: 1. a finer spectral bandpass shaping by dynamically optimizing the radio frequency (rf) driving signal, 2. an extensive calibration process, and 3. careful image preprocessing that uses calibration data to correct some well known AOTF issues in imaging applications. A novel multispectral imaging instrument is built using commercial off-the-…
Configurable Passband Imaging Spectrometer Based on Acousto-optic Tunable Filter
2008
This work presents a new configurable imaging spectrometer called Autonomous Tunable Filtering System (ATFS). The system can be configured to acquire a single narrow spectral band, a composite multispectral image, or a broad pass-band. This flexibility is given by the use of an Acousto-Optic Tunable Filter (AOTF) driven by a programmable radio frequency (rf) signal generator. The AOTF acts as a light-diffraction element which output wavelength is selected by the frequency of an rf signal applied to it. The designed rf driver is based on a high-speed Digital-to-Analog converter, which can synthesize any composite rf waveform formed by a combination of sine signals. The images are formed thro…