generalizing the hough transform to detect arbitrary shapes abstract the hough transform is a method for detecting curves by exploiting the duality between points on a curve and parameters of that curve the initial work showed how to detect both analytic curves 1 2 and non analytic curves 3 but these methods were restricted to binary edge images this work was generalized to the detection of some analytic curves in grey level images specifically lines 4 circles 5 and parabolas 6 the line detection case is the best known of these and has been ingeniously exploited in several applications 7 8 9 we show how the boundaries of an arbitrary non analytic shape can be used to construct a mapping between image space and hough transform space such a mapping can be exploited to detect instances of that particular shape in an image furthermore variations in the shape such as rotations scale changes or figure ground reversals correspond to straightforward transformations of this mapping however the most remarkable property is that such mappings can be composed to build mappings for complex shapes from the mappings of simpler component shapes this makes the generalized hough transform a kind of universal transform which can be used to find arbitrarily complex shapes

universal space time coding a universal framework is developed for constructing full rate and full diversity coherent space time codes for systems with arbitrary numbers of transmit and receive antennas the proposed framework combines space time layering concepts with algebraic component codes optimized for single input single output siso channels each component code is assigned to a thread in the space time matrix allowing it thus full access to the channel spatial diversity in the absence of the other threads diophantine approximation theory is then used in order to make the different threads transparent to each other within this framework a special class of signals which uses algebraic number theoretic constellations as component codes is thoroughly investigated the lattice structure of the proposed number theoretic codes along with their minimal delay allow for polynomial complexity maximum likelihood ml decoding using algorithms from lattice theory combining the design framework with the cayley transform allows to construct full diversity differential and noncoherent space time codes the proposed framework subsumes many of the existing codes in the literature extends naturally to time selective and frequency selective channels and allows for more flexibility in the tradeoff between power efficiency bandwidth efficiency and receiver complexity simulation results that demonstrate the significant gains offered by the proposed codes are presented in certain representative scenarios

space time block codes from orthogonal designs we introduce space time block coding a new paradigm for communication over rayleigh fading channels using multiple transmit antennas data is encoded using a space time block code and the encoded data is split into n streams which are simultaneously transmitted using n transmit antennas the received signal at each receive antenna is a linear superposition of the n transmitted signals perturbed by noise maximum likelihood decoding is achieved in a simple way through decoupling of the signals transmitted from different antennas rather than joint detection this uses the orthogonal structure of the space time block code and gives a maximum likelihood decoding algorithm which is based only on linear processing at the receiver space time block codes are designed to achieve the maximum diversity order for a given number of transmit and receive antennas subject to the constraint of having a simple decoding algorithm the classical mathematical framework of orthogonal designs is applied to construct space time block codes it is shown that space time block codes constructed in this way only exist for few sporadic values of n subsequently a generalization of orthogonal designs is shown to provide space time block codes for both real and complex constellations for any number of transmit antennas these codes achieve the maximum possible transmission rate for any number of transmit antennas using any arbitrary real constellation such as pam for an arbitrary complex constellation such as psk and qam space time block codes are designed that achieve 1 2 of the maximum possible transmission rate for any number of transmit antennas for the specific cases of two three and four transmit antennas space time block codes are designed that achieve respectively all 3 4 and 3 4 of maximum possible transmission rate using arbitrary complex constellations the best tradeoff between the decoding delay and the number of transmit antennas is also computed and it is shown that many of the codes presented here are optimal in this sense as well

convex hull based skew estimation skew estimation and page segmentation are the two closely related processing stages for document image analysis skew estimation needs proper page segmentation especially for document images with multiple skews that are common in scanned images from thick bound publications in 2 up style or postal envelopes with various printed labels even if only a single skew is concerned for a document image the presence of minority regions of different skews or undefined skew such as noise may severely affect the estimation for the dominant skew page segmentation on the other hand may need to know the exact skew angle of a page in order to work properly this paper presents a skew estimation method with built in skew independent segmentation functionality that is capable of handling document images with multiple regions of different skews it is based on the convex hulls of the individual components i e the smallest convex polygon that fully contains a component and that of the component groups i e the smallest convex polygon that fully contain all the components in a group in a document image the proposed method first extracts the convex hulls of the components segments an image into groups of components according to both the spatial distances and size similarities among the convex hulls of the components this process not only extracts the hints of the alignments of the text groups but also separate noise or graphical components from that of the textual ones to verify the proposed algorithms the full sets of the real and the synthetic samples of the university of washington english document image database i uw i are used quantitative and qualitative comparisons with some existing methods are also provided

skew estimation of document images using bagging this paper proposes a general purpose method for estimating the skew angles of document images rather than to derive a skew angle merely from text lines the proposed method exploits various types of visual cues of image skew available in local image regions the visual cues are extracted by radon transform and then outliers of them are iteratively rejected through a floating cascade a bagging bootstrap aggregating estimator is finally employed to combine the estimations on the local image blocks our experimental results show significant improvements against the state of the art methods in terms of execution speed and estimation accuracy as well as the robustness to short and sparse text lines multiple different skews and the presence of nontextual objects of various types and quantities

a robust and fast skew detection algorithm for generic documents abstract a robust and fast skew detection algorithm based on hierarchical hough transform is proposed it is capable of detecting the skew angle for various document images including technical articles postal labels handwritten text forms drawings and bar codes the algorithm is robust even when black margins introduced by photocopying are present in the image and when the document is scanned at a low resolution of 50 dpi the algorithm consists of two steps in the first step we quickly extract the centroids of connected components using a graph data structure then a hierarchical hough transform at two different angular resolutions is applied to the selected centroids the skew angle corresponds to the location of the highest peak in the hough space the performance of the algorithm is shown on a number of document images collected from various application domains the algorithm is not very sensitive to algorithmic parameters for an a4 size document image scanned at 50 dpi typically 413 575 pixels our algorithm is able to detect the skew angle with an accuracy of 0 1 in 0 4s of cpu time on a sunsparc 20 workstation

new closed form bounds on the performance of coding in correlated rayleigh fading new simple bounds are presented for the probability of error in a binary hypothesis test for communications using diversity signaling in correlated rayleigh fading the bounds are developed in the context of pairwise error event probabilities in decoding an error correction code a long standing conjecture regarding the form of worst case error events in exponentially correlated rayleigh fading is also proven the utility of the results is illustrated by their application to transfer function bounds on the probability of bit error for a system using a convolutional code the closed form transfer function bounds are shown to be tighter than previously developed transfer function bounds for communications in exponentially correlated rayleigh fading

space efficient planar convex hull algorithms a space efficient algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm we describe four space efficient algorithms for computing the convex hull of a planar point set

exact pairwise error probability of space time codes we describe a simple technique for the numerical calculation within any desired degree of accuracy of the pairwise error probability pep of space time codes over fading channels this method applies also to the calculation of e q spl radic spl xi for any nonnegative random variable spl xi whose moment generating function spl phi sub spl xi s e exp s spl xi is known its application to the multiple antenna independent rayleigh fading channel and to the rayleigh block fading channel is discussed and illustrated by two simple examples

on the generalization of the form identification and skew detection problem abstract a new method is proposed to solve the document identification and skew detection problem it can be applied to a widely used subclass of documents which resemble in style an application form unlike other approaches we make no assumptions about the nature and or style of the printed form an attempt is made to solve the problem in the most general sense the method presented here does not rely on any special features such as patterns of line crossings or dominant lines or even special symbols found only on specially designed forms the power spectral density of the horizontal projection profile of the form is used as a shift invariant feature vector the karhunen loeve transform is employed to de correlate and reduce the length of the feature vectors in the training set training is done in such a way that no rotations of the unknown form are necessary during recognition the eigenvectors of the covariance matrix of the power spectral densities for the training set along with learning vector quantization were used for training and the euclidean distance for recognition a limitation related to the amount of skew that the system can handle is alleviated with the use of a known skew detection method

space time code design for correlated ricean mimo channels at finite snr space time code stc designs commonly rely on the assumptions of independent and identically distributed i i d rayleigh channels being either slow or fast fading and high signal to noise ratio snr however it has been shown that poor scattering conditions can have detrimental effects on the performance of stcs and that the behavior of codes at high snr is radically different from the finite snr behavior this calls for new design criteria that correctly predict the behavior of codes in correlated channels at finite snr in this paper we investigate how spatially and temporally correlated ricean fading affects the performance of stcs at finite snr we derive a code design criterion leading to robust stcs in a wide variety of propagation conditions and do not require any channel knowledge at the transmitter codes satisfying this criterion are shown to perform sensibly better in correlated channels than codes designed only for i i d slow or fast rayleigh fading channels examples of space time trellis codes and algebraic codes are proposed in order to illustrate the developed criterion

remarks on space time codes including a new lower bound and an improved code this article presents a new asymptotically exact lower bound on pairwise error probability of a space time code as well as an example code that outperforms the comparable orthogonal design based space time odst code also contained in the article are an exact expression for pairwise error probability pep signal design guidelines and some observations relating to the reception of odst codes

coded modulation for a coherent ds cdma system employing an mmse receiver in a fading channel previous results have shown that high rate codes tend to yield a lower average bit error rate than low rate codes when employing a minimum mean square error mmse receiver for a direct sequence code division multiple access cdma system in either an additive white gaussian noise channel or a flat rayleigh fading channel we consider the use of larger signal constellations with both trellis coded modulation and bit interleaved coded modulation bicm to determine if further gains can be achieved in either the rayleigh or ricean fading channel the average bit error probability is derived for both coding schemes using the general ricean fading channel model based upon the common assumptions of infinite interleaving perfect channel state information and optimal mmse receiver coefficients new bounds are presented for bicm with 8 psk and 16 qam symbols which take advantage of the symmetries inherent in the signal constellations with gray code mapping in addition simulation results are presented which show the important effect a finite interleaving delay constraint has on the comparison of various codes the results show that there are cases when coded modulation does yield a significant improvement in performance for a cdma system using an mmse receiver compared to standard convolutional coding however the best coding strategy depends upon several factors including the nature of the fading process rayleigh or ricean the operating signal to noise ratio the interleaving delay constraint the time variability of the channel the number of users in the system and the severity of the near far problem

finite snr performance analysis of space time coding in correlated ricean mimo channels the performance analysis and the subsequent design of space time codes stc in multiantenna channels commonly assume an infinite signal to noise ratio snr this assumption has been shown to be justified in uncorrelated rayleigh fading channels by contrast this correspondence investigates stc in all snr regimes and in the broad class of space time correlated ricean fading multiple input multiple output mimo channels for rank deficient codes it is proven analytically that the error probability is significantly affected by spatial correlations and coherent components irrespective of the snr range and the temporal correlation for full rank codes the performance and the code design are shown to be affected by spatial correlations and or coherent paths only at finite snr in slow fading channels whereas in time varying channels they are affected in all snr regimes hence there is no guarantee that stc designed for independent and indentically distributed i i d rayleigh fading channels perform adequately in space time correlated rayleigh ricean channels simulation examples confirm the conclusions drawn from the analytical derivations they further illustrate that the use of a high snr assumption does not allow to accurately estimate the behavior of stc in practical scenarios and should thus be used with care

analysis of the error performance of trellis coded modulations in rayleigh fading channels this work presents an exact expression for the pairwise error event probability of trellis coded modulation tcm transmitted over rayleigh fading channels it includes phase shift keying psk and multilevel quadrature amplitude modulation qam codes as well as coherent and partially coherent e g differential pilot tone etc detection due to the form of the exact pairwise error event probabilities this calculation technique cannot be used with the transfer function technique to obtain an upper union bound on the overall bit error probability for this reason the authors estimate the bit error probability by considering only a small number of short error events through simulations they found that the estimation is usually very accurate at high signal to noise ratios but not as accurate at lower signal to noise ratios they study several coded modulation schemes this way among the results are the fact that tcm provides significant improvement in the error floor when detected differentially and an asymmetry in the pairwise error event probability for 16 qam

capacity scaling in mimo wireless systems under correlated fading previous studies have shown that single user systems employing n element antenna arrays at both the transmitter and the receiver can achieve a capacity proportional to n assuming independent rayleigh fading between antenna pairs we explore the capacity of dual antenna array systems under correlated fading via theoretical analysis and ray tracing simulations we derive and compare expressions for the asymptotic growth rate of capacity with n antennas for both independent and correlated fading cases the latter is derived under some assumptions about the scaling of the fading correlation structure in both cases the theoretic capacity growth is linear in n but the growth rate is 10 20 smaller in the presence of correlated fading we analyze our assumption of separable transmit receive correlations via simulations based on a ray tracing propagation model results show that empirical capacities converge to the limit capacity predicted from our asymptotic theory even at moderate n 16 we present results for both the cases when the transmitter does and does not know the channel realization

quickhulldisk a faster convex hull algorithm for disks abstract convex hull is one of the most fundamental constructs in geometry and its construction has been extensively studied there are many prior works on the convex hull of points however its counterpart for weighted points has not been sufficiently addressed despite important applications here we present a simple and fast algorithm quickhulldisk for the convex hull of a set of disks in r 2 by generalizing the quickhull algorithm for points quickhulldisk takes o nlog n time on average and o mn time in the worst case where m represents the number of extreme disks which contribute to the boundary of the convex hull of n disks these time complexities are identical to those of the quickhull algorithm for points in r 2 experimental result shows that the proposed quickhulldisk algorithm runs significantly faster than the o nlog n time incremental algorithm proposed by devillers and golin in 1995 particularly for big data quickhulldisk is approximately 2 6 times faster than the incremental algorithm for random disks and is 1 2 times faster even for the disk sets where all disks are extreme this speed up is because the basic geometric operation of the quickhulldisk algorithm is a predicate for the location of a point w r t a line and is much faster than that of the incremental algorithm the source code of quickhulldisk is freely available from mendeley data and a gui version from voronoi diagram research center hanyang university http voronoi hanyang ac kr

blind separation of superimposed moving images using image statistics we address the problem of blind separation of multiple source layers from their linear mixtures with unknown mixing coefficients and unknown layer motions such mixtures can occur when one takes photos through a transparent medium like a window glass and the camera or the medium moves between snapshots to understand how to achieve correct separation we study the statistics of natural images in the labelme data set we not only confirm the well known sparsity of image gradients but also discover new joint behavior patterns of image gradients based on these statistical properties we develop a sparse blind separation algorithm to estimate both layer motions and linear mixing coefficients and then recover all layers this method can handle general parameterized motions including translations scalings rotations and other transformations in addition the number of layers is automatically identified and all layers can be recovered even in the underdetermined case where mixtures are fewer than layers the effectiveness of this technology is shown in experiments on both simulated and real superimposed images

estimation of skew angles for scanned documents based on piecewise covering by parallelograms we propose a fast and robust skew estimation method for scanned documents that estimates skew angles based on piecewise covering of objects such as textlines figures forms or tables the method first divides a document image into a number of non overlapping slabs in which each object is covered by parallelograms it then estimates the skew angle based on these parallelograms or equivalently their complementary regions putting our method to a systematic test and comparing it with some alternatives we find that it yields favorable results in terms of accuracy sensitivity to non textual objects effectiveness in dealing with documents of unspecified reading order and computational efficiency some work is also conducted to find an effective way to further shorten its computation time at the expense of an extremely small loss of accuracy

channel coding with multilevel phase signals a coding technique is described which improves error performance of synchronous data links without sacrificing data rate or requiring more bandwidth this is achieved by channel coding with expanded sets of multilevel phase signals in a manner which increases free euclidean distance soft maximum likelihood ml decoding using the viterbi algorithm is assumed following a discussion of channel capacity simple hand designed trellis codes are presented for 8 phase shift keying psk and 16 quadrature amplitude shift keying qask modulation these simple codes achieve coding gains in the order of 3 4 db it is then shown that the codes can be interpreted as binary convolutional codes with a mapping of coded bits into channel signals which we call mapping by set partitioning based on a new distance measure between binary code sequences which efficiently lower bounds the euclidean distance between the corresponding channel signal sequences a search procedure for more powerful codes is developed codes with coding gains up to 6 db are obtained for a variety of multilevel phase modulation schemes simulation results are presented and an example of carrier phase tracking is discussed

performance bounds for coded free space optical communications through atmospheric turbulence channels error control codes can help to mitigate atmospheric turbulence induced signal fading in free space optical communication links using intensity modulation direct detection im dd error performance bound analysis can yield simple analytical upper bounds or approximations to the bit error probability we first derive an upper bound on the pairwise codeword error probability for transmission through channels with correlated turbulence induced fading which involves complicated multidimensional integration to simplify the computations we derive an approximate upper bound under the assumption of weak turbulence the accuracy of this approximation under weak turbulence is verified by numerical simulation its invalidity when applied to strong turbulence is also shown this simple approximate upper bound to the pairwise codeword error probability is then applied to derive an upper bound to the bit error probability for block codes convolutional codes and turbo codes for free space optical communication through weak atmospheric turbulence channels we also discuss the choice of interleaver length in block codes and turbo codes based on numerical evaluation of our performance bounds

achievable performance over the correlated rician channel the correlated rician channel is a useful model for a slowly fading channel in which the complex fading process is composed of two quadrature gaussian processes with a given autocorrelation function for slow fading the correlation between adjacent symbols is relatively high the authors investigate the achievable error probabilities over the channel employing coherent detection and ideal side information on the realization of the fading processes at the receiver an underlying decoding delay constraint which precludes the use of ideal interleaving is assumed coded bpsk performance is addressed both with and without the piecewise constant approximation according to which the fading value remains constant during the symbol duration for the latter case that is no piecewise constant approximation the analysis relies on the fredholm determinant associated with the fading process autocorrelation function the authors focus on the exponentially correlated channel the worst case pairs of codewords are identified the exponential behavior of the error probability with random coding and i i d gaussian inputs is analyzed and the behavior of the cut off rate and capacity is addressed the results enhance the insight to the effect of the basic parameters governing the performance and these are examined in view of previous works and compared to relevant performance results for the block fading channel model

on the performance of concatenated convolutional code and alamouti space time code with noisy channel estimates and finite depth interleaving in this paper performance of the alamouti space time code stc 1 and performance of the concatenation between the convolutional code and the alamouti stc are derived in order to describe realistic performance issues we assume that the channel estimates are calculated from linear filters using noisy pilot symbols we also assume non quasi static channels spatially correlated transmit antennas and finite depth interleaving two types of receivers are investigated for the alamouti stc namely the linear combining space time decoder lc std and the maximum likelihood space time decoder ml std two types of receivers are investigated for the concatenated system namely the lc std with the ml convolutional decoder and the joint alamouti and convolutional ml decoder the results have shown that the lc std is more sensitive to the doppler spread than the ml std however since the ml std is very sensitive to the channel estimation error the gains provided by the decoder in fast fading channels will be offset unless an optimized channel estimator is employed performance comparisons between the alamouti systems and the siso systems indicate that when the system environment is not ideal the siso systems may outperform the alamouti systems lastly analytical results are compared with simulation results to illustrate the accuracy of the analysis

blind separation of superimposed shifted images using parameterized joint diagonalization we consider the blind separation of source images from linear mixtures thereof involving different relative spatial shifts of the sources in each mixture such mixtures can be caused e g by the presence of a semi reflective medium such as a window glass across a photographed scene due to slight movements of the medium or of the sources between snapshots classical separation approaches assume either a static mixture model or a fully convolutive mixture model which are respectively either under or over parameterized for this problem in this paper we develop a specially parameterized scheme for approximate joint diagonalization of estimated spectrum matrices aimed at estimating the succinct set of mixture parameters the static gain coefficients and the shift values the estimated parameters are in turn used for convenient frequency domain separation as we demonstrate using both synthetic mixtures and real life photographs the advantage of the ability to incorporate spatial shifts is twofold not only does it enable separation when such shifts are present but it also warrants deliberate introduction of such shifts as a simple source of added diversity whenever the static mixing coefficients form a singular matrix thereby enabling separation in otherwise inseparable scenes

handwritten chinese text line segmentation by clustering with distance metric learning separating text lines in unconstrained handwritten documents remains a challenge because the handwritten text lines are often un uniformly skewed and curved and the space between lines is not obvious in this paper we propose a novel text line segmentation algorithm based on minimal spanning tree mst clustering with distance metric learning given a distance metric the connected components ccs of document image are grouped into a tree structure from which text lines are extracted by dynamically cutting the edges using a new hypervolume reduction criterion and a straightness measure by learning the distance metric in supervised learning on a dataset of pairs of ccs the proposed algorithm is made robust to handle various documents with multi skewed and curved text lines in experiments on a database with 803 unconstrained handwritten chinese document images containing a total of 8 169 lines the proposed algorithm achieved a correct rate 98 02 of line detection and compared favorably to other competitive algorithms

a lower bound to finding convex hulls given a set s of n distinct points x i y i 0 leq i n the convex hull problem is to determine the vertices of the convex hull h s all the known algorithms for solving this problem have a worst case running time of cn log n or higher and employ only quadratic tests i e tests of the form f x 0 y 0 x 1 y 1 x n 1 y n 1 0 with f being any polynomial of degree not exceeding 2 in this paper we show that any algorithm in the quadratic decision tree model must make cn log n tests for some input

block decomposition and segmentation for fast hough transform evaluation the decomposition of binary images using rectangular blocks of foreground pixels as primitives is considered based on this type of decomposition a fast method for evaluating the hough transform is introduced a complexity analysis of the proposed block hough transform algorithm sets constraints on the complexity of algorithms used for block decomposition so that the total decomposition and hough transform application time is much less than the time consumed by the usual point hough transform using this analysis we propose two algorithms for the decomposition and segmentation of binary images into rectangular blocks a combination of these methods leads to significant acceleration in the identification of linear features which is demonstrated in various image processing experiments 1999 pattern recognition society published by elsevier science ltd all rights reserved

shadow removal using bilateral filtering in this paper we propose a simple but effective shadow removal method using a single input image we first derive a 2 d intrinsic image from a single rgb camera image based solely on colors particularly chromaticity we next present a method to recover a 3 d intrinsic image based on bilateral filtering and the 2 d intrinsic image the luminance contrast in regions with similar surface reflectance due to geometry and illumination variances is effectively reduced in the derived 3 d intrinsic image while the contrast in regions with different surface reflectance is preserved however the intrinsic image contains incorrect luminance values to obtain the correct luminance we decompose the input rgb image and the intrinsic image each image is decomposed into a base layer and a detail layer we obtain a shadow free image by combining the base layer from the input rgb image and the detail layer from the intrinsic image such that the details of the intrinsic image are transferred to the input rgb image from which the correct luminance values can be obtained unlike previous methods the presented technique is fully automatic and does not require shadow detection

on the performance of space time codes over spatially correlated rayleigh fading channels we derive the exact pairwise error probability pep for space time coding over quasi static rayleigh fading channels in the presence of spatial fading correlation we show that receive correlation always degrades the pep for all signal to noise ratios snrs we quantify the effect of receive correlation by employing the notion of majorization we show that the stronger the receive correlation the worse the pep for all snrs we show that at low snr depending on the codes transmit correlation can either improve or degrade the pep performance we show that to guarantee robust performance for arbitrary transmit correlation the minimum eigenvalue of the codeword pair difference matrix should be maximized among all codeword pairs

stereo matching with linear superposition of layers in this paper we address stereo matching in the presence of a class of non lambertian effects where image formation can be modeled as the additive superposition of layers at different depths the presence of such effects makes it impossible for traditional stereo vision algorithms to recover depths using direct color matching based methods we develop several techniques to estimate both depths and colors of the component layers depth hypotheses are enumerated in pairs one from each layer in a nested plane sweep for each pair of depth hypotheses matching is accomplished using spatial temporal differencing we then use graph cut optimization to solve for the depths of both layers this is followed by an iterative color update algorithm which we proved to be convergent our algorithm recovers depth and color estimates for both synthetic and real image sequences

error performance of interleaved trellis coded psk modulations in correlated rayleigh fading channels the authors derive an exact and easily computed expression for the pairwise error event probability of interleaved coded psk modulations transmitted over channels with correlated rayleigh flat fading and additive white gaussian noise both coherent and differential detection are considered in the case of coded dpsk it is found that full interleaving does not necessarily provide the best error performance especially when the fading is relatively fast and when the autocorrelation function of the channel fading process exhibits an oscillating behavior for coherent detection or for differential detection in channels with relatively slow fading increasing the interleaving depth always improves the error performance in these cases an interleaving depth equivalent to one fifth to one quarter the duration of a fade cycle is almost as good as full interleaving

on the performance evaluation of trellis codes generating function techniques for analyzing the error event and the bit error probabilities for trellis codes are considered the conventional state diagram approach for linear codes where the number of states is equal to the number of trellis states cannot be applied directly to arbitrary trellis codes and instead a state diagram where the number of states is equal to the square of the number of trellis states must be used it is shown that for an interesting class of trellis codes a modified generating function can be defined for which the number of states em is equal to the number of trellis states the class of codes considered includes trellis codes of rate r n 1 n based upon set partitioning whenever the first partition breaks the signal constellation into two subsets which have the same configuration matrix i e the same ordered set of mutual distances the complexity of calculating this modified generating function is the same as for the ordinary generating function of a convolutional code with the same number of trellis states bounds on the performance of some interesting codes are given based upon this method

convex hull properties and algorithms abstract convex hull ch is widely used in computer graphic image processing cad cam and pattern recognition we investigate ch properties and derive new properties 1 ch vertices coordinates monotonically increase or decrease 2 the edge slopes monotonically decrease using these properties we proposed two algorithms i e ch algorithm for planar point set and ch algorithm for two available chs the main ideas of the proposed algorithms are as follows a planar point set is divided into several subsets by the extreme points and vertices in these subsets are then separately calculated during the computation the ch properties are used to eliminate concave points this can reduce the computational cost and then improves the speed our first algorithm can extract ch with o n log n time which is the lower bound of planar ch extraction and the second algorithm can obtain ch with o m n time at the worst case

bounds on the error performance of coding for nonindependent rician fading channels new upper bounds on the error performance of coded systems for rician channels are presented the fading channels need not be fully interleaved to obtain meaningful performance results these bounds hold for coherent differentially coherent and noncoherent demodulation of binary signals they provide a useful analytical approach to the evaluation of the error performance of convolutional or block coding and they may be generalized to m ary signals and trellis modulation the approach allows for complex bounds using the fine structure of the code for simpler bounds similar to those on memoryless channels and finally for a random coding bound using the cutoff rate of the channel the analysis thus permits a step by step evaluation of coded error performances for rician fading channels

hough transform based fast skew detection and accurate skew correction methods the hough transform provides a robust technique for skew detection in document images but suffers from high time complexity which becomes prohibitive for detecting skew in large documents analysis of time complexity on various stages of skew detection process is carried out in this paper a complete skew detection and correction process is divided into three parts a preprocessing stage using a simplified form of block adjacency graph bag voting process using the hough transform and de skewing the image using rotation skew correction phase which is hitherto a neglected area is analysed for the quality of de skewed images with respect to the type of rotation fast algorithms for all the three stages are presented and exhaustive analysis on time complexity is conducted it is shown that the overall time taken for the whole process is less than one second even for very large documents it is also observed that time taken in rotation is as significant as in skew detection which is reduced with the help of fast algorithms using integer operations while the bag algorithm is found to be effective for documents with roman script it does not provide satisfactory results for indian scripts where headline is a part of a script

coding for a coherent ds cdma system employing an mmse receiver in a rayleigh fading channel this paper analyzes the performance of a convolutionally coded code division multiple access system which employs a linear minimum mean square error mmse receiver for interference suppression a flat rayleigh fading channel is considered where convolutional encoding and interleaving are employed in order to combat the effects of the fading theoretical results are derived for the average bit error probability of the mmse receiver where the optimum tap weights for the adaptive filter are determined by the solution of the wiener hopf equations simulation results showing the average bit error rate of the mmse receiver are also presented which incorporate the effects of recursive least squares adaptation channel estimation using pilot symbol assisted modulation and finite interleaving results show that the mmse receiver with coding can provide a substantial gain over the matched filter receiver in a rapidly varying rayleigh fading channel the results also reiterate the fact that lower rate codes are not necessarily the best choice when used with the mmse receiver

tight analytical and asymptotic upper bound for the ber and fer of linear codes over exponentially correlated generalized fading channels in this paper the upper bound and asymptotical approximation for the bit error rate ber as well as for the frame error rate of linear block codes under maximum likelihood decoding operating over exponentially correlated ec generalized fading channels are proposed particularly our analysis takes the convolutional codes as an example and three different fading scenarios are considered namely rice nakagami m and weibull fading such scenarios have a common property that is spherically invariant random process sirp our analysis relies on the derivation of new lower bounds per each eigenvalue since the ber as well as the fer expressions are written in terms of the pairwise error probability which by its turn depends on the eigenvalues of the channel covariance matrix based on that the upper bounds and asymptotic expressions of the considered metrics subject to the three above fading models are derived which show to be tighter than the previous results published elsewhere in the literature especially for the high signal to noise ratio regions

automatic image orientation detection we present an algorithm for automatic image orientation estimation using a bayesian learning framework we demonstrate that a small codebook the optimal size of codebook is selected using a modified mdl criterion extracted from a learning vector quantizer lvq can be used to estimate the class conditional densities of the observed features needed for the bayesian methodology we further show how principal component analysis pca and linear discriminant analysis lda can be used as a feature extraction mechanism to remove redundancies in the high dimensional feature vectors used for classification the proposed method is compared with four different commonly used classifiers namely k nearest neighbor support vector machine svm a mixture of gaussians and hierarchical discriminating regression hdr tree experiments on a database of 16 344 images have shown that our proposed algorithm achieves an accuracy of approximately 98 on the training set and over 97 on an independent test set a slight improvement in classification accuracy is achieved by employing classifier combination techniques

contour and texture analysis for image segmentation this paper provides an algorithm for partitioning grayscale images into disjoint regions of coherent brightness and texture natural images contain both textured and untextured regions so the cues of contour and texture differences are exploited simultaneously contours are treated in the intervening contour framework while texture is analyzed using textons each of these cues has a domain of applicability so to facilitate cue combination we introduce a gating operator based on the texturedness of the neighborhood at a pixel having obtained a local measure of how likely two nearby pixels are to belong to the same region we use the spectral graph theoretic framework of normalized cuts to find partitions of the image into regions of coherent texture and brightness experimental results on a wide range of images are shown

dynamic planar convex hull operations in near logarithmic amortized time we give a data structure that allows arbitrary insertions and deletions on a planar point set p and supports basic queries on the convex hull of p such as membership and tangent finding updates take o log 1 e n amori tzed time and queries take o log n time each where n is the maximum size of p and e is any fixed positive constant for some advanced queries such as bridge finding both our bounds increase to o log 3 2 n the only previous fully dynamic solution was by overmars and van leeuwen from 1981 and required o log 2 n time per update and o log n time per query

design of interchannel mrf model for probabilistic multichannel image processing in this paper we present a novel framework that exploits an informative reference channel in the processing of another channel we formulate the problem as a maximum a posteriori estimation problem considering a reference channel and develop a probabilistic model encoding the interchannel correlations based on markov random fields interestingly the proposed formulation results in an image specific and region specific linear filter for each site the strength of filter response can also be controlled in order to transfer the structural information of a channel to the others experimental results on satellite image fusion and chrominance image interpolation with denoising show that our method provides improved subjective and objective performance compared with conventional approaches

affine invariant comparison of point sets using convex hulls and hausdorff distances many object recognition or identification applications involve comparing features associated with point sets this paper presents an affine invariant point set matching technique which measures the similarity between two point sets by embedding them into an affine invariant feature space the developed technique assumes no a priori knowledge of reference points as is the case in many identification problems reference points of a point set are obtained based on its convex hull an enhanced version of the modified hausdorff distance is also introduced and used in the feature space for comparing two point sets it should be noted that the technique does not attempt to obtain correspondences between the point sets the introduced technique is applied to two real databases and its performance is found favorable as compared to three other affine invariant matching techniques

impact of diversity reception on fading channels with coded modulation i coherent detection we address the problem of designing and analyzing the performance of a coded modulation scheme for the fading channel when space diversity is used under fairly general conditions a channel affected by fading can be turned into an additive white gaussian noise awgn channel by increasing the number of diversity branches consequently it can be expected and is indeed verified by our analyses and simulations that a coded modulation scheme designed to be optimal for the awgn channel also will perform asymptotically well on a fading channel with diversity this paper presents bounds on the bit error probability of a system with coded modulation and diversity for space and time correlated rician flat fading specifically we derive a new method which allows evaluation of the pairwise error probability extremely easily as well as accurately and computationally fast the accuracy achieved improves considerably on the widely used but rather loose chernoff bound starting from this analysis we study the asymptotic behavior of the fading channel with diversity as the number of diversity branches increases and we address the effects of diversity on coded modulation performance and design criteria including the effect on interleaver depth which affects the total delay of the system

robust estimation of motion blur kernel using a piecewise linear model blur kernel estimation is a crucial step in the deblurring process for images estimation of the kernel especially in the presence of noise is easily perturbed and the quality of the resulting deblurred images is hence degraded since every motion blur in a single exposure image can be represented by 2d parametric curves we adopt a piecewise linear model to approximate the curves for the reliable blur kernel estimation the model is found to be an effective tradeoff between flexibility and robustness as it takes advantage of two extremes 1 the generic model represented by a discrete 2d function which has a high degree of freedom dof for the maximum flexibility but suffers from noise and 2 the linear model which enhances robustness and simplicity but has limited expressiveness due to its low dof we evaluate several deblurring methods based on not only the generic model but also the piecewise linear model as an alternative after analyzing the experiment results using real world images with significant levels of noise and a benchmark data set we conclude that the proposed model is not only robust with respect to noise but also flexible in dealing with various types of blur

robust algorithms for constructing strongly convex hulls in parallel given a set s of n points in the plane an e strongly convex hull of s is defined as a convex polygon p with the vertices taken from s such that no point of s lies farther than outside p and such that even if the vertices of p are perturbed by as much as e p remains convex this paper presents the first parallel robust method for this generalized convex hull problem note that the convex hull of s is the 0 strongly convex 0 hull of s we show that an e strongly convex o e hull of s can be constructed in o log3n time using n processors with imprecise computations where is the error unit of primitive operations this result also implies an improved sequential algorithm our algorithm consists of two parts 1 computing a convex o e hull of n points in o log3n time using n processors and 2 constructing an e strongly convex o e hull of a convex polygon with n vertices in o log2n time with n processors we also find an approximate bridge of two sets with n points each in o log2n time using n processors which we use as a subroutine all these algorithms are fundamental and have their own applications the parallel computational model in this paper is the erew pram

user assisted separation of reflections from a single image using a sparsity prior when we take a picture through transparent glass the image we obtain is often a linear superposition of two images the image of the scene beyond the glass plus the image of the scene reflected by the glass decomposing the single input image into two images is a massively ill posed problem in the absence of additional knowledge about the scene being viewed there are an infinite number of valid decompositions in this paper we focus on an easier problem user assisted separation in which the user interactively labels a small number of gradients as belonging to one of the layers even given labels on part of the gradients the problem is still ill posed and additional prior knowledge is needed following recent results on the statistics of natural images we use a sparsity prior over derivative filters this sparsity prior is optimized using the iterative reweighted least squares irls approach our results show that using a prior derived from the statistics of natural images gives a far superior performance compared to a gaussian prior and it enables good separations from a modest number of labeled gradients

adaptive detection of ds cdma signals in fading channels this paper examines the behavior of the minimum mean squared error mmse receiver in frequency nonselective fading channels it is noted that the mmse receiver will often lose phase lock on the desired signal when the desired signal dips into a deep fade a modification to the mmse receiver is presented which is demonstrated to function quite nicely in flat fading channels analytical results for the modified mmse receiver are presented and found to agree very well with simulation results these analytical results are then compared to the theoretical performance of the conventional i e correlator receiver in terms of both bit error rate ber and capacity as expected the modified mmse receiver was found to offer a substantial improvement in both ber and capacity finally a simple empirically derived formula is given which will give a good approximation to the ber of the modified mmse receiver in a rayleigh fading environment this formula can also be used to determine the number of users a given system can support it is noted that as e sub b n sub 0 grows it is quite feasible to approach 100 channel utilization with the mmse receiver whereas a conventional receiver is typically limited to a utilization of 10 20

a theory for multiresolution signal decomposition the wavelet representation multiresolution representations are effective for analyzing the information content of images the properties of the operator which approximates a signal at a given resolution were studied it is shown that the difference of information between the approximation of a signal at the resolutions 2 sup j 1 and 2 sup j where j is an integer can be extracted by decomposing this signal on a wavelet orthonormal basis of l sup 2 r sup n the vector space of measurable square integrable n dimensional functions in l sup 2 r a wavelet orthonormal basis is a family of functions which is built by dilating and translating a unique function psi x this decomposition defines an orthogonal multiresolution representation called a wavelet representation it is computed with a pyramidal algorithm based on convolutions with quadrature mirror filters wavelet representation lies between the spatial and fourier domains for images the wavelet representation differentiates several spatial orientations the application of this representation to data compression in image coding texture discrimination and fractal analysis is discussed