Marco Anisetti

Designing of a type-2 fuzzy logic filter for improving edge-preserving restoration of interlaced-to-progressive conversion

This paper focuses on recently advanced fuzzy models and the application of type-2 fuzzy sets in video deinterlacing. The final goal of the proposed deinterlacing algorithm is to exactly determine an unknown pixel value while preserving the edges and details of the image. To begin, we will discuss some artefacts of spatial, temporal, and spatio-temporal domain deinterlacing methods. In order to address the aforementioned issues, we adopted type-2 fuzzy sets concepts to design a weight evaluating approach. In the proposed method, the upper and lower fuzzy membership functions of the type-2 fuzzy logic filters are derived from the type-1 (or primary) fuzzy membership function. The weights from upper and lower membership functions are considered to be multiplied with the candidate deinterlaced pixels. Experimental results proved that the performance of the proposed method was superior, both objectively and subjectively to other different conventional deinterlacing methods. Moreover, the proposed method preserved the smoothness of the original image edges and produced a high-quality progressive image.

Concept of Linguistic Variable-Based Fuzzy Ensemble Approach: Application to Interlaced HDTV Sequences

This paper addresses the problem of edge restoration in digital images. Taking advantage of an ensemble approach, multiple type-1 fuzzy filters are combined to reach a decision. The fuzzy logic concept for linguistic variables and possibility theory is discussed with regard to knowledge representation and inference procedures. To improve conventional deinterlacing issues, we adopt type-1 fuzzy set concepts to design a weight-measuring approach. We demonstrate that the fuzzy ensemble approach model is well suited to image processing and provide case studies in the video-deinterlacing field. In our proposed method, five fuzzy membership functions (MFs) of linguistic variable-based fuzzy logic filters are derived from the type-1 (a.k.a. ordinary or primary) fuzzy MF. The weight-measuring process of our proposed model is used to assign weights to six candidate deinterlaced pixels (CDPs) that are interpolated according to edge direction. The use of a different MF for each direction allows the filter to characterize each pixel variation influence independently, according to its direction. The weights from all MFs are multiplied with the CDPs. The results of the empirical trials clearly show that the proposed system can successfully deal with several image types containing motion or detail elements.

Map-Based Location and Tracking in Multipath Outdoor Mobile Networks

Technical enhancements of mobile technologies are paving the way to the definition of high-quality and accurate geolocation solutions based on data collected and managed by GSM/3G networks. We present a technique that provides geolocation and mobility prediction both at network and service level, does not require any change to the existing mobile network infrastructure, and is entirely performed on the mobile network side, making it more robust than other positioning systems with respect to location spoofing and other terminal-based security threats. Our approach is based on a novel database correlation technique over Received Signal Strength Indication (RSSI) data, and provides a geolocation and tracking technique based on advanced map- and mobility-based filtering. The performance of the geolocation algorithm has been carefully validated by an extensive experimentation, carried out on real data collected from the mobile network antennas of a complex urban environment.

Fuzzy rough sets hybrid scheme for motion and scene complexity adaptive deinterlacing

Current research activities in the field of deinterlacing include the selection of suitable deinterlacing methods and the estimation of the exact value of a missing line. This paper proposes a spatio-temporal domain fuzzy rough sets rule for selecting a deinterlacing method that is suitable for regions with high motion or frequent scene changes. The proposed algorithm consists of two parts. The first part is fuzzy rule-based edge-direction detection with an edge preserving part that utilizes fuzzy theory to find the most accurate edge direction and interpolates the missing pixels. Using the introduced gradients in the interpolation, the vertical resolution in the deinterlaced image is subjectively concealed. The second part of the proposed algorithm is a rough sets-assisted optimization which selects the most suitable of five different deinterlacing methods and successively builds approximations of the deinterlaced sequence. Moreover, this approach employs a size reduction of the database system, keeping only the information essential for the process. The proposed algorithm is intended not only to be fast, but also to reduce deinterlacing artifacts.

Specification of the Geometric Regularity Model for Fuzzy If-Then Rule-Based Deinterlacing

A fuzzy if-then rule-based intra-field deinterlacing method using geometric duality is presented in this paper. The proposed method is a content-based hybrid scheme switching between the well-known edge-based linear average method and the proposed geometric duality-based deinterlacing method. Conventional deinterlacing methods usually employ edge-based interpolation techniques within pixel-based estimations. However, they are somewhat sensitive to noise and intensity variations in the image. Moreover, their performance is visually unacceptable due to their failure to estimate edge direction. To reduce this sensitivity, the proposed algorithm investigates features from low-resolution images, and applies them to high-resolution images to calculate the missing pixels. We analyzed properties of the missing pixels and modeled them using geometric regularity. Depending on the features of the region, the missing pixels were interpolated in different ways. The proposed algorithm is computationally feasible and promises to be a good candidate for a low-cost hardware interpolator.

Fuzzy Rule-Based Edge-Restoration Algorithm in HDTV Interlaced Sequences

This paper proposes an interpolation algorithm for conversion from the interlaced to the progressive scanning format. The proposed algorithm consists of two parts: an edge direction detection part and a fuzzy rule-based edge-restoration interpolation part. The different types of edge, peak, and monotonic slope patterns are considered in a spatial domain interpolation strategy. Edges with a certain vertical component look preserved in the interpolation using a fuzzy rule-based algorithm. The vertical resolution in the interpolated image is subjectively concealed by introducing vertical gradients in the interpolation. Computer simulations verify the effective performance of this image processing technology.

A test-based security certification scheme for web services

The Service-Oriented Architecture (SOA) paradigm is giving rise to a new generation of applications built by dynamically composing loosely coupled autonomous services. Clients (i.e., software agents acting on behalf of human users or service providers) implementing such complex applications typically search and integrate services on the basis of their functional requirements and of their trust in the service suppliers. A major issue in this scenario relates to the definition of an assurance technique allowing clients to select services on the basis of their nonfunctional requirements and increasing their confidence that the selected services will satisfy such requirements. In this article, we first present an assurance solution that focuses on security and supports a test-based security certification scheme for Web services. The certification scheme is driven by the security properties to be certified and relies upon a formal definition of the service model. The evidence supporting a certified property is computed using a model-based testing approach that, starting from the service model, automatically generates the test cases to be used in the service certification. We also define a set of indexes and metrics that evaluate the assurance level and the quality of the certification process. Finally, we present our evaluation toolkit and experimental results obtained applying our certification solution to a financial service implementing the Interactive Financial eXchange (IFX) standard.

Fuzzy Weighted Approach to Improve Visual Quality of Edge-Based Filtering

A new algorithm for the deinterlacing of interlaced scanned video sequences is presented in this paper. The ultimate goal of the proposed algorithm is to exactly determine the unknown pixel value while preserving the edges and details of the image. Traditional edge direction-based interpolation algorithms usually introduce artifacts in the case of non-clear edges. In order to solve the above issues, we adopted fuzzy concepts to design a weight-evaluating technique. The weights were considered to be multiplied by the candidate deinterlaced pixels. Experimental results demonstrated that the resulting frames contained less errors and sharper edges than frames generated using common approaches such as median filtering and edge direction-based linear interpolation.

A rank-ordered marginal filter for deinterlacing.

This paper proposes a new interpolation filter for deinterlacing, which is achieved by enhancing the edge preserving ability of the conventional edge-based line average methods. This filter consists of three steps: pre-processing step, fuzzy metric-based weight assignation step, and rank-ordered marginal filter step. The proposed method is able to interpolate the missing lines without introducing annoying articles. Simulation results show that the images filtered with the proposed algorithm restrain less annoying pixels than the ones acquired by other methods.

Rough Sets-Assisted Subfield Optimization for Alternating Current Plasma Display Panel

Plasma display panel technology employs a pulse-number modulation method to generate the gradation of the display. However, this method can create a false contour distortion when moving pictures are reproduced. In this paper, we propose an effective subfield optimization technique which is based on measuring motion picture distortion. To this end, we propose two applications of the measurements. One is optimum selection of the codewords to improve performance, and the other is the application of rough sets theory to subfield optimization, which reduces computational CPU time. Simulation results show that dynamic false contouring can be effectively reduced by this optimization technique, and the complexity can be minimized, using rough sets theory.