Publicații

2020

1. Datcu, O., Macovei, C., Hobincu, R., "Chaos based cryptographic pseudo-random number generator template with dynamic state change", , pp. None, , DOI:10.3390/app10020451, 2020

   Rezumat:

   This article presents a configurable, high-throughput pseudo-random number generator template targeting cryptographic applications. The template is parameterized using a chaotic map that generates data, an entropy builder that is used to periodically change the parameters of the map and a parameter change interval, which is the number of iterations after which the entropy builder will change the generator's parameters. The system is implemented in C++ and evaluated using the TestU01 and NIST RNG statistical tests. The same implementation is used for a stream cipher that can encrypt and decrypt PNG images. A Monte-Carlo analysis of the seed space was performed. Results show that for certain combinations of maps and entropy builders, more than 90% of initial states (seeds) tested pass all statistical randomness tests. Also, the throughput is large enough so that a 8 K color image can be encrypted in 2 s on a modern laptop CPU (exact specifications are given in the paper). The conclusion is that chaotic maps can be successfully used as a building block for cryptographic random number generators. © 2020 by the authors.

Sus

2019

1. Radu Hobincu Octaviana Datcu Corina Macovei , "Entropy global control for a chaos based pRNG", , pp. 432-435, , DOI:10.1109/TSP.2019.8768818, 2019

   Rezumat:

   Abstract: In this paper, we have attempted to resolve an important issue present in a previously proposed cryptographic pseudo-random number generator (pRNG), the issue being that for certain seeds values, the behavior of the system is not random. To solve this problem, he have added a global control system that gathers entropy and periodically alters the current internal state of the generator in order to prevent lack of randomness in the output values. The new system is empirically tested with an established randomness test battery, NIST, as well as through Monte-Carlo simulations. The results show that for almost all of the tested seeds, the output exhibits random properties.
2. O. Datcu R. Hobincu C. Macovei , "Genetic algorithms for high-order sliding-mode observers", , pp. 305-308, , DOI:10.1109/SMICND.2019.8923857, 2019

   Rezumat:

   Abstract: A previous work proposed a chaos-based private communication scheme. A fourth order differentiator was used to estimate the dynamics of the transmitter, when only one of its states is measured at the receiving end. The choice for the parameters of this estimator was done empirically, evaluating the errors between the original and the estimated evolution. This work adds to this procedure a genetic algorithm which allows an automatization of the decision regarding the values of the parameters which enable the best reconstruction.
3. Ovidiu Plugariu Lucian Petrica Radu Pirea Radu Hobincu , "Hadoop ZedBoard cluster with GZIP compression FPGA acceleration", , pp. None, , DOI:10.1109/ECAI46879.2019.9042006, 2019

   Rezumat:

   Abstract: This paper presents the implementation of a heterogeneous Hadoop cluster based on the Zynq ZedBoard development platform with GZIP FPGA offloading for high-speed and energy efficient computing. We have developed the first open source FPGA GZIP compressor, designed for educational and research purposes, that can reach 1 Gbps compression speed using a 125 MHz clock. The core uses only 10% of the Zynq-7020 SoC FPGA resources and is 5.7x faster than the ARM CPU which runs at 667 MHz. We implemented an eight-node Hadoop distributed cluster and performed the Wordcount and Terasort benchmarks using software and hardware GZIP compression during the Map stage. Results show an almost 2x more energy-efficient cluster when compression is done using our GZIP FPGA core than using the software compression. The performance of the Hadoop cluster is limited by the 512 MB of RAM and the low read-write speed of the SD cards which act as hard drives for each node.
4. Mǎlǎescu, A., Duţu, L.C., Sultana, A., Filip, D., Ciuc, M., "Improving in-car emotion classification by NIR database augmentation", , pp. None, , DOI:10.1109/FG.2019.8756628, 2019

   Rezumat:

   On-board detection of driver's emotions has become a task of high importance for car manufacturers, as negative emotions appear to be one of the major risks for car accidents. Deep neural networks have become over the last years the state of the art methods for computer vision and image classification. Yet, their success depends upon their being trained on a comprehensive database, which should cover all of the real-life situations that may arise in practice. Most of the in-car driver monitoring cameras capture images in the near infra-red (NIR) domain therefore one needs a large database with images featuring emotions in the NIR domain. As most databases featuring human emotions contain images acquired in the visible domain, we discuss in this paper two methods of transferring the NIR-like look into the "visible" images, by using a CycleGAN style-transferring neural network trained using "paired" and "unpaired" images. We show that the resulted database augmented with NIR-like images leads to a much improved performance in emotion classification for a deep neural network, when tested on real NIR images. © 2019 IEEE.
5. Octaviana Datcu Radu Hobincu Corina Macovei , "Singular value decomposition to determine the dynamics of a chaotic regime oscillator", , pp. 119-122, , DOI:10.1109/SMICND.2019.8923805, 2019

   Rezumat:

   Abstract: Targeting the hybrid analog-digital private communication field, this paper aims to estimate the parameters of an analog circuit model. An oscilloscope stores the samples of a voltage in a.csv file. The data series is processed using a digital signal technique the singular value decomposition. Singular values and corresponding right-eigenvectors are used to estimated the values of the parameters of the model characterizing the circuit that produced the measured output. The decomposition is performed using small windows of samples of the output of a jerk-type circuit from the literature and an averaging operation improves the estimation.

Sus

2018

1. Ionuţ Fîciu Radu Stîlpeanu Cosmin ţoca Anca Petre Carmen Pătraşcu Mihai Ciuc , "Automatic Annotation of Object Instances by Region-Based Recurrent Neural Networks", , pp. None, , DOI:10.1109/ICCP.2018.8516608, 2018

   Rezumat:

   Abstract: In recent years, a wide variety of automatic, semiautomatic and manual approaches to image annotation have been proposed. These prerequisites have been driven by continuous advances of deep learning algorithms that often encounter the problem of insufficient or inappropriate training data, as well as sub-par markings' accuracy which can have a direct impact on the model's performance regardless. The main contribution of this paper is the development of a complex annotation framework able to automatically generate high-quality markings. The annotation work-flow aims to be an iterative process allowing automatic labeling of object bounding boxes, while simultaneously predicting the polygon outlining the object instance inside the box. The markings' format is fully compatible with COCO Detection & Panoptic APIs that provide open-source interfaces for loading, parsing, and visualizing annotations. Following the completion of the research project funding this research, the code will be publicly available.
2. Datcu, O., Hobincu, R., Stanciu, M., Badea, R.A., "Encrypting multimedia data using modified baptista’s chaos-based algorithm", , pp. 185-190, , DOI:10.1007/978-3-319-92213-3_27, 2018

   Rezumat:

   One of the easiest to implement, yet complex, symmetric key chaos-based ciphers is the one proposed by Baptista in 1998. It has attracted much interest from scholars, who underlined its deficiencies and proposed different methods to enhance it. The present paper proposes an additional step in the encryption procedure - a modulo two sum between the binary representations of Baptista’s cryptograms and that of the value of the chaotic logistic map at that very iteration. This results in a flat distribution of the cryptograms. Thus, one of the major drawbacks of Baptista’s cryptosystem, the exponential decay of the repartition of the cyphertext values, is surmounted. The original Baptista’s algorithm is described, the proposed method is exemplified on a short message and its results are discussed when applied on multimedia files. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
3. Hobincu, R., Datcu, O., "FPGA Implementation of a Chaos Based PRNG Targetting Secret Communication", , pp. None, , DOI:10.1109/ISETC.2018.8583863, 2018

   Rezumat:

   This paper describes the digital implementation of a chaos based cyptographic pseudo-random number generator using a Zynq SoC, offloading the computation to the FPGA. The implementation is based on the generalized Henon map, and it is done using fixed point 3.61 arithmetic. We will show that there is a performance improvement compared to the execution on the ARM Cortex A9 processor and that the generated random bytes are consistent with the software implementation. The generator is tested against the NIST, Dieharder and TestU01 suites. © 2018 IEEE.
4. Petre, A.I., Toca, C., Patrascu, C., Ciuc, M., "Improving public datasets markings' quality using unsupervised refinement kernels", , pp. 299-302, , DOI:10.1145/3203217.3205862, 2018

   Rezumat:

   In recent years there has been an exponential growth in developing machine learning algorithms, focused on applications ranging from scene understanding, to the more standard object recognition and classification tasks. Although multiple approaches have been proposed for solving these issues, a common prerequisite is the existence of large datasets, which can be used both for training and testing purposes. We propose a semi-automatic annotation framework for object instances, which addresses the problems related to the big data paradigm in the context of object detection and pixel-level segmentation. The designed marking and learning workflow aims to be a cyclical process allowing iterative improvements of the marking architecture. Results of this processing chain are empirically validated on the COCO database. © 2018 Association for Computing Machinery.

Sus

2017

1. Neghina, M., Rasche, C., Ciuc, M., Sultana, A., Tiganesteanu, C., "Automatic detection of cervical cells in Pap-smear images using polar transform and k-means segmentation", , pp. None, , DOI:10.1109/IPTA.2016.7821038, 2017

   Rezumat:

   We introduce a novel method of cell detection and segmentation based on a polar transformation. The method assumes that the seed point of each candidate is placed inside the nucleus. The polar representation, built around the seed, is segmented using k-means clustering into one candidate-nucleus cluster, one candidate-cytoplasm cluster and up to three miscellaneous clusters, representing background or surrounding objects that are not part of the candidate cell. For assessing the natural number of clusters, the silhouette method is used. In the segmented polar representation, a number of parameters can be conveniently observed and evaluated as fuzzy memberships to the non-cell class, out of which the final decision can be determined. We tested this method on the notoriously difficult Pap-smear images and report results for a database of approximately 20000 patches. © 2016 IEEE.
2. Serban Oprisescu Mihai Ciuc Alina Sultana , "Automatic measurement of infantile hemangiomas", , pp. 503-506, , DOI:10.1109/EHB.2017.7995471, 2017

   Rezumat:

   Abstract: Infantile hemangiomas (IH) are a type of benign vascular tumors that appear within the first 5 months of life. The assessment of lesion size and its evolution in time is done manually by the physician, using a ruler, and this measurement is not very accurate. This paper presents a method for automatic measurement of the IH size. The work is divided in two parts: automatic computation of the size of one millimeter in pixels, based on the Hough transform and the total variation, and automatic segmentation based on K-means clustering and a 2D total variation filtered image. The segmentation performance was evaluated on 20 IH images and a mean border error of 13.56% was obtained.
3. Octaviana Datcu Radu Hobincu Lucian Petrică , "Baptista's chaos-based cipher implemented in a field programmable gate array", , pp. 191-194, , DOI:10.1109/SMICND.2017.8101196, 2017

   Rezumat:

   Abstract: In the context of the current struggle for information security and computational efficacy, this paper studies Baptista's chaos-based encryption cipher as a resource-efficient alternative to the more popular block cipher algorithms. We evaluate the cipher by encrypting different types of data - text, images and sound - and we present the analysis of cyphertext statistical distribution and obfuscation characteristics. Simulation results illustrate the effectiveness of the algorithm on multimedia content. We present an implementation of the cipher as a digital system in a Xilinx Zynq 7000 series FPGA, and evaluate hardware resource utilization and maximum obtainable frequency. The cipher source code - Matlab simulation and the Verilog hardware description - is made available as a GIT repository. The aim of the demarche is to provide digital circuitry which may be easily integrated in a hybrid analog-digital cryptosystem which employs a dynamically changing secret key.

Sus

2016

1. Cătălina Neghină Marta Zamfir Mihai Ciuc Alina Sultana, "Automatic Detection of Hemangioma through a Cascade of Self-organizing Map Clustering and Morphological Operators", , pp. 145-150, , DOI:https://doi.org/10.1016/j.procs.2016.07.023, 2016

   Rezumat:

   Abstract In this paper we propose a method for the automatic detection of hemangioma regions, consisting of a cascade of algorithms: a Self Organizing Map (SOM) for clustering the image pixels in 25 classes (using a 5x5 output layer) followed by a morphological method of reducing the number of classes (MMRNC) to only two classes: hemangioma and non-hemangioma. We named this method SOM-MMRNC. To evaluate the performance of the proposed method we have used Fuzzy C-means (FCM) for comparison. The algorithms were tested on 33 images; for most images, the proposed method and FCM obtain similar overall scores, within one percent of each other. However, in about 18% of the cases, there is a significant increase of the overall score for SOM-MMRNC (over 3.5%). On average, the results obtained with the proposed cascade are 1.06% better for each image.
2. Catalina Neghina Marta Zamfir Mihai Ciuc Alina Sultana Maria Popescu , "Automatic monitoring system for the detection and evaluation of the evolution of hemangiomas", , pp. None, , DOI:10.1109/IPTA.2016.7820981, 2016

   Rezumat:

   Abstract: In this paper we introduce an automatic monitoring system for the detection and the evaluation of the evolution of hemangiomas using a fuzzy logic system based on two parameters: area and redness. We have considered pairs of images (from two different moments in time) that show hemangiomas either evolving, stationary or regressing. The starting points of the algorithm are the rectangular regions of interest (ROI), manually selected for each of the two images, and automatically segmented using Fuzzy C-means. Using the area and the redness of the hemagiomas extracted with Fuzzy C-means, for the same patient, at different moments of time, the algorithm decides whether the hemangioma is evolving, stationary or regressing. Because it is also useful to understand how the tumor's shape is changing in time, we have also included a method of matching and overlapping the hemangioma regions.
3. Oprisescu, S., Ciuc, M., Sultana, A., Vasile, I., "Automatic segmentation of infantile hemangiomas within an optimally chosen color space", , pp. None, , DOI:10.1109/EHB.2015.7391592, 2016

   Rezumat:

   Infantile hemangiomas (IH) are benign vascular tumors, most of them appearing in the first weeks and developing until six months of age. The evaluation of the lesion size is usually made by the physician through manual measurement, which is inaccurate. This paper presents an algorithm for the automatic segmentation of the hemangioma region, relying on the Maximum a Posteriori (MAP) classification method. The segmentation result is improved by regularization with discrete Markov fields (MAP-Markov). Then, a further improvement is performed, by eliminated distant non-hemangioma pixels. The optimal color space is chosen before segmentation, from five different color spaces, by iteratively computing the segmentation error 10 times on each color space and each of the 40 images from the database. The segmentation performance is evaluated in terms of border error. © 2015 IEEE.
4. Ştefan, G.M., Bîra, C., Hobincu, R., Maliţa, M., "FPGA-based programmable accelerator for hybrid processing", , pp. 148-165, , 2016

   Rezumat:

   The emergence of CPU/FPGA hybrid processors promotes the FPGA accelerators as circuits which perform the critical functions associated to an application. As circuits, they are designed and optimized by hardware designers or, with a debatable efficiency, by specialized compilers. We propose, as an intermediate solution, to use a predesigned parameterized family of programmable generic structures, ready to be synthesized in FPGA technology as highly parallel computing engines able to perform efficiently data intense computations. The solution loses, in the worst cases, tens of percent of the processing power, compared with optimized hardware design, but gains a lot in flexibility allowing the number of skilled users to increase with few orders of magnitude. The proposed solution supposes to select, from a family of predesigned structures, an appropriate RTL module, to implement it in FPGA, and to program the resulting parallel engine in a high-level programming language by a software designer. The theoretical foundation for the generic family of parallel engines is grounded on the synergy between Stephen Kleene's computational model of Partial Recursive Functions and the Functional Programming Systems proposed by John Backus.

Sus

2015

1. Serban Oprisescu Tiberiu Rădulescu Alina Sultana Christoph Rasche Mihai Ciuc , "Automatic pap smear nuclei detection using mean-shift and region growing", , pp. None, , DOI:10.1109/ISSCS.2015.7203961, 2015

   Rezumat:

   Abstract: The Babes-Papanicolaou test (also known as Pap smear) is a method of cervical cancer screening used to detect abnormal cells which are or can become cancerous. Since the visual inspection of pap smears is very time consuming, the need for automatic methods is required. This paper presents an algorithm for the automatic detection of nuclei within pap smears images. The algorithm relies in the highly effective mean-shift filtering method which enhances the contrast of nuclei areas. The segmentation consists of a region growing with starting points taken from the image gradient map. Size and eccentricity measures are used to keep only nuclei from the segmented regions. The method is validated on two different pap smear test databases and the detection rate is above 91%.
2. Alina Sultana Marta Zamfir Mihai Ciuc Şerban Oprişescu Maria Popescu , "Automatic segmentation of infantile hemangiomas", , pp. None, , DOI:10.1109/ISSCS.2015.7203960, 2015

   Rezumat:

   Abstract: Infantile hemangiomas are the most common types of tumors that are found in infants and have an incidence of approximately 10% in the common population. Although most infantile hemangiomas are self-involuting, due to their fast proliferation they may threaten vital anatomical structures and physiological functions; also, the involution process may take up to several years. An accurate monitoring of the progress of hemangioma growth and regression is essential. We thus suggest using a computer aided follow-up monitoring of these lesions by an automatic detection and quantifying the lesion dynamic: regression or proliferation. In this study we propose some image enhancements methods and also a preliminary color based segmentation. We have tested our methods on 25 hemangioma cases and compared the automated segmentation results with clinician-determined segmentation using an area percentage error.
3. Cosmin Ţoca Carmen Pătraşcu Mihai Ciuc , "Performance testing and functional limitations of Normalized Autobinomial Markov Channels", , pp. 401-405, , DOI:10.1109/ICCP.2015.7312692, 2015

   Rezumat:

   Abstract: The field of pedestrian detection has gained momentum in recent years, due to a large range of applications, including advanced robotics, aided surveillance and automotive safety. Its importance in the field of computer vision is confirmed by the large number of available algorithms, as well as the increased complexity of the public databases used for testing. To comply with the increased demands of the field, we perform extensive performance testing of the proposed Normalized Autobinomial Markov Channels (NAMC) algorithm using the Caltech Pedestrian Dataset. The proposed solution aims at isolating easily distinguishable body characteristics by learning contextual probabilistic dependencies. The functional limitations of the algorithm are derived by separately analyzing three test scenarios: scale, occlusion, aspect ratio. The obtained results demonstrate the efficiency of our approach, especially in the case of heavy occlusions, where the algorithm ranks first among the tested state-of-the art solutions.

Sus

2014

1. Oprisescu, S., Ciuc, M., Vasile, I., "Hand posture recognition using the intrinsic dimension", , pp. 974-979, , DOI:10.1109/OPTIM.2014.6850920, 2014

   Rezumat:

   This paper presents a hand posture recognition algorithm based on the intrinsic dimension (ID). Hand segmentation is reliable with cluttered background due to the use of the time-of-flight (ToF) range camera. The hand pose recognition is performed using an image indexing technique with a reference database of 360 images. The database and the query images consist of nine types of hand postures. The similarity measure used for finding the best match with the query image is the correlation between the 1D representations of the 2D ID hand contours. The average recognition rate is above 96%, which is satisfactory. © 2014 IEEE.
2. Alina Sultana Ioana Dumitrache Mihai Vocurek Mihai Ciuc , "Removal of artifacts from dermatoscopic images", , pp. None, , DOI:10.1109/ICComm.2014.6866757, 2014

   Rezumat:

   Abstract: Dermoscopy is the primary tool used for pigmented skin lesion diagnosis. Despite the use of this relative new clinical method dermoscopy based, diagnose is still subjective and the diagnosis detection accuracy is about 75-80%. In this paper we present several enhancement pre-processing techniques applied on dermatoscopic images, such as black frame removal and hair removal in an automatically manner. We have tested our algorithms on 45 dermoscopic images and compared the automated enhancement methods results with other existing methods.

Sus

2012

1. Alina Sultana Mihai Ciuc Tiberiu Radulescu Liu Wanyu Diana Petrache , "Preliminary work on dermatoscopic lesion segmentation", , pp. 2273-2277, , 2012

   Rezumat:

   Abstract: Dermoscopy has become the primary tool used for pigmented skin lesion diagnosis providing better quality and accurate images. Computer-Assisted Image Interpretation is a new direction that involves the automatical lesion detection, feature extraction and classification (benign or malignant). This paper refers to several prior pre-processing enhancement techniques and an automated segmentation method. We have tested our methods on 60 dermoscopic images and compared the automated segmentation results with dermatologist-determined segmentation using an area percentage error.

Sus

2011

1. Sultana, A.E., Ciuc, M., "Detection of mammographic masses using a refined mean shift approach", , pp. None, , 2011

   Rezumat:

   Mammography is one of the available methods for early detection of abnormalities, which is related to the human breast cancer. Image segmentation plays an important role in breast cancer detection. This paper presents a refined mean shift segmentation approach using spatial information characteristics as well, in order to achieve some accurate detection results. © 2011 GR T Popa University.

Sus

2010

1. Alina Sultana Mihai Ciuc Rodica Strungaru Laura Florea , "A new approach in breast image registration", , pp. 149-154, , DOI:10.1109/ICCP.2010.5606447, 2010

   Rezumat:

   Abstract: According to the World Health Organization, breast cancer is the most common cancer suffered by women in the world, which during the last two decades, has increased the women mortality in developing countries. Mammography is the best method used for the screening; the problem of detecting possible cancer areas is very complex due, on one hand, to the diversity in shape of the ill tissue and, on the other hand, to the poorly defined border between the healthy and the cancerous zone. An automated technique for the alignment of right and left breast images has been developed for use in the computerized analysis of bilateral breast images. Using this technique, the breast region is firstly identified by using an adaptive thresholding algorithm. The focus is on determining control points in the two mamograms; these points are used to put the two mammograms into correspondence. The algorithm's performance was evaluated on a large number of difficult cases and found to be adequate.
2. Alina Sultana Mihai Ciuc Rodica Strungaru , "Detection of pectoral muscle in mammograms using a mean-shift segmentation approach", , pp. 165-168, , DOI:10.1109/ICCOMM.2010.5509003, 2010

   Rezumat:

   Abstract: Detection of pectoral muscle in mammograms is an important pre-processing segmentation step. The pectoral muscle is one of the few anatomical features that appears clearly and reliably in medio-lateral oblique view mammograms. This new method overcomes the limitation of the straight-line representation considered in our initial investigation using the Hough transform.
3. Valeriu Codreanu Radu Hobincu , "Performance gain from data and control dependency elimination in embedded processors", , pp. 47-50, , DOI:10.1109/ISETC.2010.5679319, 2010

   Rezumat:

   Abstract: This paper presents a way of increasing overall performance in embedded processors by introducing a multithreading interleaved execution model that can be applied to any Instruction Set Architecture. Usual acceleration techniques as superpipeline or branch prediction are not suited for embedded machines due to their inherent inefficiency. We will show that by removing dependencies within a processor and thus eliminating the need for extra hardware required for keeping the overall coherence, there will be a noticeable increase in performance (up to 450%) and also a decrease in size and power consumption. Also, this approach will maintain the backwards compatibility with the software legacy in order to keep the software changes to a minimum.
4. Petronela Bumbăcea Valeriu Codreanu Radu Hobincu Lucian Petrică Gheorghe M. Ştefan , "Technology driven architecture for integral parallel embedded computing", , pp. 35-42, , DOI:10.1109/SMICND.2010.5650942, 2010

   Rezumat:

   Abstract: The computational structures are not able to scale following the increased number of components offered by the technological development driven by the Moore's law. In order to use efficiently the emerging nanotechnologies new architectural approaches are requested. Thus, new technology driven architectures must be developed. The proposed architecture is designed in this technologically evolving context, to support the increasing computational diversity, complexity and intensity requested in the emergent domain of parallel embedded computing. The resulting physical embodiment has at least two orders of magnitude higher effective GIPS/Watt and GIPS/mm 2 than the currently produced structures. This new architectural approach is based on ConnexArray ™ technology, already developed and tested on real chips, and on the Bubble-free Embedded Architecture for Multithreading execution model. The paper proposes a computational platform able to manage tens of threads and a number of execution/processing units which starts from tens and goes up to thousands.

Sus

2007

1. Serban Oprisescu Dragos Falie Mihai Ciuc Vasile Buzuloiu , "Measurements with ToF Cameras and Their Necessary Corrections", , pp. None, , DOI:10.1109/ISSCS.2007.4292691, 2007

   Rezumat:

   Abstract: The most important characteristic of time-of-flight (ToF) cameras is the ability to measure the distance to each image pixel. Thus, for each pixel, information on both its amplitude and distance to the camera are available. However, technological problems inherent to the acquisition principle lead to inaccuracies in estimating both characteristics: on one hand, there are errors in estimating the distance, especially for far-distance pixels. On the other hand, the detected amplitude decreases with the distance. Part of these inaccuracies are corrected with special camera-calibration software. In this paper, we propose two methods that attempt to further correct each information based on the other one. First, the amplitude image is enhanced by using distance information: a pixel-wise, distance-based correction of the amplitude brings to light details otherwise unnoticeable. Secondly, an amplitude-based distance modification corrects some of the distance estimation errors for far-distance pixels.

Sus

2004

1. C. Vertan A. Stoica C. Fernandez-Maloigne M. Ciuc , "Objective image quality measures by planar glyph representation", , pp. 1317-1320, , 2004

   Rezumat:

   Abstract: The commonly used non-perceptual image quality measures are mainly derived from pixel-to-pixel differences and closely relate to the mean squared error. Recently, there has been an increased interest in the evaluation of neighborhood-based differences between images, that take into account the local (spatial) image context. This contribution proposes the use of such local context information for the evaluation of image quality or inter-image differences by the planar glyph representation of multivariate data and the induced geometric-inspired difference measures.

Sus

1997

1. Ciuc, M., Coquin, D., Bolon, P., "Quantitative assessment of two skeletonization algorithms adapted to rectangular grids", , pp. 588-595, , DOI:10.1007/3-540-63507-6_249, 1997

   Rezumat:

   In this paper, an adaptation to rectangular grids of two skeletonization algorithms is presented Skeletonizations are quantitatively compared by using Baddeley's distance between the original pattern and the one reconstructed from the skeleton. © Springer-Verlag Berlin Heidelberg 1997.

Sus