nils-herrmann/clean_scirepeval huggingface dataset:
A stochastic nearest neighbor character prototype approach for online writer identification

One novel technique for identifying the writer of an online handwritten document is proposed. This technique makes use of a character prototype distribution to model the specific allographs used by a given writer. In this paper, we propose to extend and improve upon this newly established methodology by S.K. Chan et al (2008) by making use of a stochastic nearest neighbor algorithm to estimate the character prototype distribution. The proposed method is text independent and relies on the automatic segmentation of the handwritten text at the character level. Our results show that this approach attained a writer identification rate of 99.2% when a reference database of 120 writers is used. Experiments related to the effect of the length of text of the document on the performance of the writer identification system are also reported.
Blurred Image Splicing Localization by Exposing Blur Type Inconsistency

In a tampered blurred image generated by splicing, the spliced region and the original image may have different blur types. Splicing localization in this image is a challenging problem when a forger uses some postprocessing operations as antiforensics to remove the splicing traces anomalies by resizing the tampered image or blurring the spliced region boundary. Such operations remove the artifacts that make detection of splicing difficult. In this paper, we overcome this problem by proposing a novel framework for blurred image splicing localization based on the partial blur type inconsistency. In this framework, after the block-based image partitioning, a local blur type detection feature is extracted from the estimated local blur kernels. The image blocks are classified into out-of-focus or motion blur based on this feature to generate invariant blur type regions. Finally, a fine splicing localization is applied to increase the precision of regions boundary. We can use the blur type differences of the regions to trace the inconsistency for the splicing localization. Our experimental results show the efficiency of the proposed method in the detection and the classification of the out-of-focus and motion blur types. For splicing localization, the result demonstrates that our method works well in detecting the inconsistency in the partial blur types of the tampered images. However, our method can be applied to blurred images only.
Performance analysis of an FFH/BFSK product-combining receiver under multitone jamming

The performance of a fast frequency-hopped binary frequency-shift keying (FFH/BFSK) spread-spectrum (SS) communication system is studied in this paper. The FFH system employs a product-combining receiver against the worst case multitone jamming (MTJ) and additive white Gaussian noise (AWGN). The compact characteristic functions of the natural logarithm of the product-combiner outputs are obtained based on the Taylor series expansion. The characteristic functions are then used to derive the bit error rate (BER) expressions that are applicable to higher diversity levels. Our analysis, validated by the simulation results, shows that the band MTJ is generally more harmful than the corresponding independent MTJ. The BER performance of the product-combining receiver is shown to possess good MTJ rejection capability compared to that of the soft-decision linear-combining receiver, especially under both moderate and strong MTJ power conditions.
Data Hiding For Binary Images Authentication By Considering A Larger Neighborhood

This paper proposes a novel data hiding method for binary images authentication aims at preserving the connectivity of pixels in a local 3times3 neighborhood and dynamically improving the "flipppability" decision by considering a larger neighborhood. The interlaced morphological binary wavelet transform (IMBWT) is employed as the basic processing tool. The primary objective of considering a larger neighborhood is to improve the visual quality of the watermarked image. The post-checking constraints ensure that the "embeddability" of a pixel is invariant in the data embedding process thus facilitates blind watermark extraction and incorporation of the cryptographic signature. "Single flipping" and "pair flipping" are discussed. The "connectivity-preserving" and "transition change" patterns are properly paired and classified so that each category is isolated from other categories, hence no ambiguity exists. The "end stroke" patterns that are orthogonal to the "connectivity-preserving" and "transition change" patterns are employed such that a double data hiding scheme can be designed.
Fingerprint Combination for Privacy Protection

We propose here a novel system for protecting fingerprint privacy by combining two different fingerprints into a new identity. In the enrollment, two fingerprints are captured from two different fingers. We extract the minutiae positions from one fingerprint, the orientation from the other fingerprint, and the reference points from both fingerprints. Based on this extracted information and our proposed coding strategies, a combined minutiae template is generated and stored in a database. In the authentication, the system requires two query fingerprints from the same two fingers which are used in the enrollment. A two-stage fingerprint matching process is proposed for matching the two query fingerprints against a combined minutiae template. By storing the combined minutiae template, the complete minutiae feature of a single fingerprint will not be compromised when the database is stolen. Furthermore, because of the similarity in topology, it is difficult for the attacker to distinguish a combined minutiae template from the original minutiae templates. With the help of an existing fingerprint reconstruction approach, we are able to convert the combined minutiae template into a real-look alike combined fingerprint. Thus, a new virtual identity is created for the two different fingerprints, which can be matched using minutiae-based fingerprint matching algorithms. The experimental results show that our system can achieve a very low error rate with FRR = 0.4% at FAR = 0.1%. Compared with the state-of-the-art technique, our work has the advantage in creating a better new virtual identity when the two different fingerprints are randomly chosen.
Modeling the EXIF-Image correlation for image manipulation detection

EXchangeable Image File format (EXIF) is a metadata header containing shot-related camera settings such as aperture, exposure time, ISO speed etc. These settings can affect the photo content in many ways. In this paper, we investigate the underlying EXIF-Image correlation and propose a novel model, which correlates image statistical noise features with several commonly used EXIF features. By formulating each EXIF feature as a weighted combination of different image statistical noise features, we first select a compact image statistical noise feature set using sequential floating forward selection. The underlying correlation as a set of regression weights is then solved using a least squares solution. When applying our learned correlation to detect image manipulation, we achieve average test accuracies of 94.6%, 94.1% and 94.9% in three different cameras to detect the presence of common image brightness and contrast adjustment.
No-Reference Image Blur Assessment Based on Discrete Orthogonal Moments

Blur is a key determinant in the perception of image quality. Generally, blur causes spread of edges, which leads to shape changes in images. Discrete orthogonal moments have been widely studied as effective shape descriptors. Intuitively, blur can be represented using discrete moments since noticeable blur affects the magnitudes of moments of an image. With this consideration, this paper presents a blind image blur evaluation algorithm based on discrete Tchebichef moments. The gradient of a blurred image is first computed to account for the shape, which is more effective for blur representation. Then the gradient image is divided into equal-size blocks and the Tchebichef moments are calculated to characterize image shape. The energy of a block is computed as the sum of squared non-DC moment values. Finally, the proposed image blur score is defined as the variance-normalized moment energy, which is computed with the guidance of a visual saliency model to adapt to the characteristic of human visual system. The performance of the proposed method is evaluated on four public image quality databases. The experimental results demonstrate that our method can produce blur scores highly consistent with subjective evaluations. It also outperforms the state-of-the-art image blur metrics and several general-purpose no-reference quality metrics.
Semi-fragile watermarking for text document images authentication

The proposed novel semi-fragile watermarking method makes use of prioritized noise suppression patterns; it takes into account the smoothness and connectivity in a 5/spl times/5 neighborhood. This is particularly necessary when the original text document image is noisy. The content signature watermark is generated by uniquely mapping the binary bit pattern in each block to a binary bit. A novel way of embedding the content signature watermark in each block is proposed which is effective in detecting malicious attacks. Shuffling is applied to the host image to increase the security of the algorithm. A minimum flipping distance is imposed to control the visual quality. Experimental results validate the arguments made.
Performance of rejection filters in DS spread-spectrum systems

It is well known that the insertion of a linear rejection filter at the receiver improves the performance of a direct-sequence spread-spectrum system against narrow-band interference. The authors consider both the transversal filter and the prediction-error filter, and compute their bit error rates which include the effect of intersymbol interference. From the numerical results obtained, they effectively estimate the tone jammer and minimize its effect in the incoming signal. Also, adding a linear rejection filter to a direct-sequence spread-spectrum system is more effective than increasing the processing gain.<<ETX>>
Extending the sound impulse response of room using extrapolation

An analytic method is used to extend the sound impulse response of a room. It is based on the extrapolation theory for band-limited signals. Only two matrix operations are needed for extending a discrete impulse response. Due to the approximation of the geometrical acoustic model of the observed data and the computation errors, the problem may be ill-conditioned. The optimum regularization method is used to solve the ill-posed problem. For discrete signals, the extrapolation is not unique, therefore additional constraints are used to obtain the admissible result. The method is evaluated with a set of psychoacoustic experiments. The evaluations are made on five psychological characteristics, and a general conclusion is given based on general fuzzy clustering.
Backward-forward distortion minimization for binary images data hiding

In our previous paper, we propose to use the morphological transform for binary images data hiding for authentication purpose. We view flipping an edge pixel in binary images as shifting the edge location one pixel horizontally and vertically. Based on this observation, we propose an interlaced morphological binary wavelet transform to track the shifted edges. The two processing cases that flipping the candidates of one does not affect the flippability conditions of another are employed such that a large capacity can be achieved. However, employing double processing cases sacrifices the visual quality of the watermarked image. In this paper, we further investigate and propose a novel effective Backward-Forward Minimization method to minimize the visual distortion for double processing cases. Experimental results demonstrate its superior performance.
Partial-band jamming rejection of FFH/BFSK with product combining receiver over a Rayleigh-fading channel

An exact closed-form expression of the characteristic function is derived for a fast frequency-hopping (FFH) binary orthogonal frequency-shift-keying (FSK) spread-spectrum (SS) communication system. The FFH system employs a product combining receiver over a Rayleigh-fading channel with partial-band jamming and additive white Gaussian noise (AWGN). The derived characteristic function is then used to obtain a compact bit error rate (BER) expression for different diversity levels. Our study shows that there exists an optimum diversity level under certain channel conditions.
Multitone jamming rejection of FFH/BFSK spread-spectrum system over fading channels

Analytical expressions for bit-error probability are derived for a fast frequency-hopping binary frequency-shift keying (FFH/BFSK) spread-spectrum communication system over a fading channel with worst-case band multitone jamming (MTJ) and additive white Gaussian noise (AWGN). An FFH system employing either a linear-combining receiver or a clipper receiver is investigated. The desired signal and MTJ are assumed to undergo independent fading, and our analysis, validated with simulation results, shows that the performance of the system is slightly improved as the severity of the MTJ fading is increased. The clipper receiver is found to be superior to the linear-combining receiver when the jamming power is strong. The worst-case MTJ is shown to be more harmful than the corresponding worst-case partial-band noise jamming over a fading channel with AWGN.
Impact of Alphabet Knowledge on Online Writer Identification

Character prototype approaches for writer identification produces a consistent set of templates that are used to model the handwriting styles of writers, thereby allowing high accuracies to be attained. This paper extends such work on writer identification by investigating the usage of alphabet knowledge derived from the character prototypes. In addition, we demonstrate the concept of discriminative power of alphabets. It is not unconceivable that certain alphabets allow writers to express their individuality of handwriting with a more distinct and unique style compared with other alphabets. This paper establishes that such alphabets have higher discriminative powers in identifying writers. Experiments related to the reduction in dimensionality of the writer identification system are also reported. Our results show that the discriminative power of alphabet can be used to reduce the complexity while maintaining the same level of performance for the writer identification system.
The threshold analysis of SVD-based algorithms

The problem of analyzing the threshold effect of signal processing algorithms which use the singular-value decomposition (SVD) is addressed. The probability of obtaining an outlier is calculated and used to determine the threshold SNR at which the variance of parameter estimation errors depart from Cramer-Rao bound behavior. Simulation results using low rank approximation and linear prediction for frequency estimation verify the analysis. The same method of analysis can be applied to a broad class of parameter-estimation methods in which the principal-component technique or low rank approximations to matrices are used.<<ETX>>
Attack using reconstructed fingerprint

Most fingerprint recognition systems store minutiae-based fingerprint template in a database. As the minutiae template is very compact, many take it for granted that these minutiae points do not contain sufficient information for reconstructing the original fingerprint. This paper proposes a scheme to reconstruct the fingerprint from minutiae points based on the amplitude and frequency modulated (AM-FM) fingerprint model to fool a system that requires a full print. We first generate a binary ridge pattern which has a similar ridge flow to that of the original fingerprint. The continuous phase is intuitively reconstructed by removing the spirals in the phase image estimated from the ridge pattern. We further introduce a phase refinement process to reduce the artifacts created due to the discontinuity in the reconstructed phase image, which is the combination of the continuous phase and the spiral phase (computed from the minutiae points). Compared with previous works, our reconstructed fingerprint matches better against the original fingerprint and the other impressions. In addition, it contains fewer artifacts.
DS-CDMA synchronization with dual-antenna in unknown correlated noise

We consider the propagation delay estimation of a direct-sequence code-division multiple-access (DS-CDMA) system in unknown correlated noise. The new propagation delay estimation method proposed here is based on generalized correlation decomposition (GCD). First, the received signal with a dual-antenna through a flat-fading channel is modeled. Then, two GCD-based propagation delay estimators: dual-antenna singular value decomposition (SVD) and dual-antenna canonical correlation decomposition (CCD) estimators are presented and compared with common MUSIC estimator. Simulation results show that the proposed estimators, especially the dual-antenna CCD estimator, are robust against the near-far problem and outperform the common MUSIC estimator in unknown correlated noise.
Efficient Image Sharpness Assessment Based on Content Aware Total Variation

State-of-the-art sharpness assessment methods are mostly based on edge width, gradient, high-frequency energy, or pixel intensity variation. Such methods consider very little the image content variation in conjunction with the sharpness assessment which causes the sharpness metric to be less effective for different content images. In this paper, we propose an efficient no-reference image sharpness assessment called content aware total variation (CATV) by considering the importance of image content variation in sharpness measurement. By parameterizing the image TV statistics using generalized Gaussian distribution, the sharpness measure is identified by the standard deviation, and the image content variation evaluator is indicated by the shape parameter. However, the standard deviation is content-dependent which is different for the regions with strong edges, high frequency textures, low frequency textures, and blank areas. By incorporating the shape-parameter in moderating of the standard deviation, we propose a content aware sharpness metric. The experimental results show that the proposed method is highly correlated with the human vision system and has better sharpness assessment results than the state-of-the-art techniques on the blurred subset images of LIVE, TID2008, CSIQ, and IVC databases. Also, our method has very low computational complexity which is suitable for online applications. The correlations with the subjective of the four databases and statistical significance analysis reveal that our method has superior results when compared with previous techniques.
A new adaptive neural network multiuser detector in synchronous CDMA systems

A new adaptive neural network multiuser detector is proposed and investigated for synchronous code-division multiple-access (CDMA) systems. The proposed multiuser detector includes two parts: a decorrelating detector as its auxiliary detector and an adaptive multiple layer perceptron (MLP) detector as its main detector. At the setup stage, the auxiliary detector detects the user's transmitted data and at the same time feeds these output data to the main MLP detector as its training data, and the main detector is trained by using the well-known backpropagation (BP) algorithm. After the training process, the auxiliary detector stops work and the main detector starts detecting the user's transmitted data self-adaptively. The proposed detector is blind and can provide near minimum bit-error-rate performance.
Combined polynomial transform and radix-q algorithm for MD discrete W transform

The type-II r-dimensional discrete W transform (rD-DWT-II) with size q/sup l1//spl times/q/sup l2//spl times//spl middot//spl middot//spl middot//spl times//sup lr/ q where q is an odd prime number, is converted into a series of one-dimensional (1-D) reduced DWT-IIs by using the multidimensional polynomial transform and an index permutation. Then, a radix-q algorithm and a cyclic convolution algorithm are presented for the computation of the 1-D reduced DWT-IIs. The new fast algorithm substantially reduces the overall computational complexity compared with the row-column method. Especially, the number of multiplications required by the proposed algorithm for computing an rD-DWT-II is only 1/r times that needed by the commonly used row-column method.
Analysis of estimation of signal parameters by linear-prediction at high SNR using matrix approximation

A greatly simplified calculation of the accuracy of estimates of the parameters of exponential signals is introduced. The authors assume that the estimates are obtained by first estimating the coefficients of a prediction-error filter (PEF) that arises in signal modeling by linear prediction. A simplified approach based on matrix approximation is used to calculate the statistics of the errors in the estimated signal parameters at high SNR. This approach provides insights for design and tractable formulas even for the case of multicomponent signals and Hankel or Toeplitz data matrices. The analyses are verified by simulation examples that include single- and multiple-component signals consisting of damped or undamped complex exponential signals in noise.<<ETX>>
Privacy Protection of Fingerprint Database

A fingerprint authentication system for the privacy protection of the fingerprint template stored in a database is introduced here. The considered fingerprint data is a binary thinned fingerprint image, which will be embedded with some private user information without causing obvious abnormality in the enrollment phase. In the authentication phase, these hidden user data can be extracted from the stored template for verifying the authenticity of the person who provides the query fingerprint. A novel data hiding scheme is proposed for the thinned fingerprint template. This scheme does not produce any boundary pixel in the thinned fingerprint during data embedding. Thus, the abnormality caused by data hiding is visually imperceptible in the marked-thinned fingerprint. Compared with using existing binary image data hiding techniques, the proposed method causes the least abnormality for a thinned fingerprint without compromising the performance of the fingerprint identification.
Statistical analysis of state-space approach in harmonic retrieval

The author presents a statistical analysis of the performance of the state-variable balancing for estimating the parameters of exponential signals in the presence of additive noise. The case of frequency estimation for a single damped sinusoid is carried out in detail because the analysis can be presented more clearly; the formulas are simpler and provide insight; and the results are applicable in radar, sonar, communication, and data modelling. Analytical expressions for the variances of the frequency estimate at high signal-to-noise ratios is derived. Both analytical and experimental results are presented to illustrate the performance of the state-variable balancing method.
FFT-based self-normalising receiver for FFH spread spectrum systems

Partial-band interference due to intentional and unintentional jamming in fast frequency-hopping spread-spectrum (FFH/SS) systems can be effectively suppressed by additional signal processing techniques. The authors present the performance analysis of a binary frequency-shift-keying SS system in conjunction with a fast Fourier transform (FFT) processor. The FFT-based self-normalising receiver, requiring no knowledge of signal and jamming levels, also enjoys the advantages provided by modern digital signal processing technology. Numerical results show that the receiver performance is better than that of the square-law linear combining receiver and comparable to that of the conventional self-normalising receiver as well as the clipper receiver.