Abstract: Image convolution similar to the receptive fields
found in mammalian visual pathways has long been used in
conventional image processing in the form of Gabor masks.
However, no VLSI implementation of parallel, multi-layered pulsed
processing has been brought forward which would emulate this
property. We present a technical realization of such a pulsed image
processing scheme. The discussed IC also serves as a general testbed
for VLSI-based pulsed information processing, which is of interest
especially with regard to the robustness of representing an analog
signal in the phase or duration of a pulsed, quasi-digital signal, as
well as the possibility of direct digital manipulation of such an
analog signal. The network connectivity and processing properties
are reconfigurable so as to allow adaptation to various processing
tasks.
Abstract: The goal of this paper is to find Wardrop equilibrium
in transport networks at case of uncertainty situations, where the
uncertainty comes from lack of information. We use simulation tool
to find the equilibrium, which gives only approximate solution, but
this is sufficient for large networks as well. In order to take the
uncertainty into account we have developed an interval-based
procedure for finding the paths with minimal cost using the
Dempster-Shafer theory. Furthermore we have investigated the users-
behaviors using game theory approach, because their path choices
influence the costs of the other users- paths.
Abstract: Facial expression analysis is rapidly becoming an
area of intense interest in computer science and human-computer
interaction design communities. The most expressive way humans
display emotions is through facial expressions. In this paper we
present a method to analyze facial expression from images by
applying Gabor wavelet transform (GWT) and Discrete Cosine
Transform (DCT) on face images. Radial Basis Function (RBF)
Network is used to classify the facial expressions. As a second stage,
the images are preprocessed to enhance the edge details and non
uniform down sampling is done to reduce the computational
complexity and processing time. Our method reliably works even
with faces, which carry heavy expressions.
Abstract: In a BFWA (Broadband Fixed Wireless Access Network) the evolved SINR (Signal to Interference plus Noise Ratio) is relevant influenced by the applied duplex method. The TDD (Time Division Duplex), especially adaptive TDD method has some advantage contrary to FDD (Frequency Division Duplex), for example the spectrum efficiency and flexibility. However these methods are suffering several new interference situations that can-t occur in a FDD system. This leads to reduced SINR in the covered area what could cause some connection outages. Therefore, countermeasure techniques against interference are necessary to apply in TDD systems. Synchronization is one way to handling the interference. In this paper the TDD systems – applying different system synchronization degree - will be compared by the evolved SINR at different locations of the BFWA service area and the percentage of the covered area by the system.
Abstract: In this paper we examine the use of global texture analysis based approaches for the purpose of Persian font recognition in machine-printed document images. Most existing methods for font recognition make use of local typographical features and connected component analysis. However derivation of such features is not an easy task. Gabor filters are appropriate tools for texture analysis and are motivated by human visual system. Here we consider document images as textures and use Gabor filter responses for identifying the fonts. The method is content independent and involves no local feature analysis. Two different classifiers Weighted Euclidean Distance and SVM are used for the purpose of classification. Experiments on seven different type faces and four font styles show average accuracy of 85% with WED and 82% with SVM classifier over typefaces
Abstract: In this paper, we present a method for edge
segmentation of satellite images based on 2-D Phase Congruency
(PC) model. The proposed approach is composed by two steps: The
contextual non linear smoothing algorithm (CNLS) is used to smooth
the input images. Then, the 2D stretched Gabor filter (S-G filter)
based on proposed angular variation is developed in order to avoid
the multiple responses in the previous work. An assessment of our
proposed method performance is provided in terms of accuracy of
satellite image edge segmentation. The proposed method is compared
with others known approaches.
Abstract: This work presents a fusion of Log Gabor Wavelet
(LGW) and Maximum a Posteriori (MAP) estimator as a speech
enhancement tool for acoustical background noise reduction. The
probability density function (pdf) of the speech spectral amplitude is
approximated by a Generalized Laplacian Distribution (GLD).
Compared to earlier estimators the proposed method estimates the
underlying statistical model more accurately by appropriately
choosing the model parameters of GLD. Experimental results show
that the proposed estimator yields a higher improvement in
Segmental Signal-to-Noise Ratio (S-SNR) and lower Log-Spectral
Distortion (LSD) in two different noisy environments compared to
other estimators.