Search results for: Handwritten word recognition
608 Comparing Sumerograms in Akkadian and Arameograms in Middle Persian
Authors: Behzad Moeini Sam, Sara Mohammadi Avandi
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Ancient scribes usually wrote an Akkadian word in Akkadian, spelling it out syllable by syllable. Sometimes, however, they wrote down the equivalent word in Sumerian for the Akkadians held Sumerian culture, from which they had inherited the cuneiform script, in high esteem. ‘Syllabic’ vs. ‘Sumerographic’ are the two forms of cuneiform writing. The Assyrian language was a branch of the Akkadian one that used the script and language of Aramaic throughout the whole of the empire. It caused the Aramaic language to apply as an Interlingua until the following periods. This paper aims to compare Sumerograms in Akkadian texts and Arameograms in Middle Persian texts to find a continuous written system that continued to apply from Akkadian to the Middle Persian. It will firstly introduce Sumerograms which are the earliest Akkadian texts, and will finally explain the Aramaic language, which continues its use by the Parthians and Sasanians as Arameograms. Thus, the main conclusion to be drawn is that just as the Akkadians who applied Sumerograms, Parthian and Pahlavi (including the inscriptions and the Psalter), too, employed a large number of, and more or less faithfully rendered, Aramaic words, also called Arameograms.
Keywords: Sumerogram, Mesopotamian, Akkadian. Aramaic, Middle Persian.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 346607 Alphanumeric Hand-Prints Classification: Similarity Analysis between Local Decisions
Authors: G. Dimauro, S. Impedovo, M.G. Lucchese, R. Modugno, G. Pirlo
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This paper presents the analysis of similarity between local decisions, in the process of alphanumeric hand-prints classification. From the analysis of local characteristics of handprinted numerals and characters, extracted by a zoning method, the set of classification decisions is obtained and the similarity among them is investigated. For this purpose the Similarity Index is used, which is an estimator of similarity between classifiers, based on the analysis of agreements between their decisions. The experimental tests, carried out using numerals and characters from the CEDAR and ETL database, respectively, show to what extent different parts of the patterns provide similar classification decisions.
Keywords: Handwriting Recognition, Optical Character Recognition, Similarity Index, Zoning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1293606 A New Method of Combined Classifier Design Based on Fuzzy Neural Network
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To make the modulation classification system more suitable for signals in a wide range of signal to noise rate (SNR), a novel method of designing combined classifier based on fuzzy neural network (FNN) is presented in this paper. The method employs fuzzy neural network classifiers and interclass distance (ICD) to improve recognition reliability. Experimental results show that the proposed combined classifier has high recognition rate with large variation range of SNR (success rates are over 99.9% when SNR is not lower than 5dB).Keywords: Modulation classification, combined classifier, fuzzy neural network, interclass distance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1211605 An Advanced Method for Speech Recognition
Authors: Meysam Mohamad pour, Fardad Farokhi
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In this paper in consideration of each available techniques deficiencies for speech recognition, an advanced method is presented that-s able to classify speech signals with the high accuracy (98%) at the minimum time. In the presented method, first, the recorded signal is preprocessed that this section includes denoising with Mels Frequency Cepstral Analysis and feature extraction using discrete wavelet transform (DWT) coefficients; Then these features are fed to Multilayer Perceptron (MLP) network for classification. Finally, after training of neural network effective features are selected with UTA algorithm.Keywords: Multilayer perceptron (MLP) neural network, Discrete Wavelet Transform (DWT) , Mels Scale Frequency Filter , UTA algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2339604 A Method for Iris Recognition Based on 1D Coiflet Wavelet
Authors: Agus Harjoko, Sri Hartati, Henry Dwiyasa
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There have been numerous implementations of security system using biometric, especially for identification and verification cases. An example of pattern used in biometric is the iris pattern in human eye. The iris pattern is considered unique for each person. The use of iris pattern poses problems in encoding the human iris. In this research, an efficient iris recognition method is proposed. In the proposed method the iris segmentation is based on the observation that the pupil has lower intensity than the iris, and the iris has lower intensity than the sclera. By detecting the boundary between the pupil and the iris and the boundary between the iris and the sclera, the iris area can be separated from pupil and sclera. A step is taken to reduce the effect of eyelashes and specular reflection of pupil. Then the four levels Coiflet wavelet transform is applied to the extracted iris image. The modified Hamming distance is employed to measure the similarity between two irises. This research yields the identification success rate of 84.25% for the CASIA version 1.0 database. The method gives an accuracy of 77.78% for the left eyes of MMU 1 database and 86.67% for the right eyes. The time required for the encoding process, from the segmentation until the iris code is generated, is 0.7096 seconds. These results show that the accuracy and speed of the method is better than many other methods.Keywords: Biometric, iris recognition, wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1891603 Lexical Database for Multiple Languages: Multilingual Word Semantic Network
Authors: K. K. Yong, R. Mahmud, C. S. Woo
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Data mining and knowledge engineering have become a tough task due to the availability of large amount of data in the web nowadays. Validity and reliability of data also become a main debate in knowledge acquisition. Besides, acquiring knowledge from different languages has become another concern. There are many language translators and corpora developed but the function of these translators and corpora are usually limited to certain languages and domains. Furthermore, search results from engines with traditional 'keyword' approach are no longer satisfying. More intelligent knowledge engineering agents are needed. To address to these problems, a system known as Multilingual Word Semantic Network is proposed. This system adapted semantic network to organize words according to concepts and relations. The system also uses open source as the development philosophy to enable the native language speakers and experts to contribute their knowledge to the system. The contributed words are then defined and linked using lexical and semantic relations. Thus, related words and derivatives can be identified and linked. From the outcome of the system implementation, it contributes to the development of semantic web and knowledge engineering.
Keywords: Multilingual, semantic network, intelligent knowledge engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1950602 An Efficient Motion Recognition System Based on LMA Technique and a Discrete Hidden Markov Model
Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier
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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.Keywords: Human Motion Recognition, Motion representation, Laban Movement Analysis, Discrete Hidden Markov Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 711601 Iris Recognition Based On the Low Order Norms of Gradient Components
Authors: Iman A. Saad, Loay E. George
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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.
Keywords: Iris recognition, contrast stretching, gradient features, texture features, Euclidean metric.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1954600 Antecedents of Word-of-Mouth for Meat with Traceability: Evidence from Thai Consumers
Authors: Kawpong Polyorat, Nathamon Buaprommee
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Because of the outbreak of mad cow disease and bird flu, consumers have become more concerned with quality and safety of meat and poultry. As a consequence, meat traceability has been implemented as a tool to raise the standard in the meat production industry. In Thailand, while traceability is relatively common among the manufacturer-wholesaler-retailers cycle, it is rarely used as a marketing tool specifically designed to persuade consumers who are the actual meat endusers. Therefore, the present study attempts to understand what influences consumers to spread their words-of-mouth (WOM) regarding meat with traceability by conducting a study in Thailand where research in this area is rather scant. Data were collected from one hundred and sixty-seven consumers in the northeastern region and analyzed with SEM. The study results reveal that perceived usefulness of traceability system, social norms, and product class knowledge are significant antecedents where consumers spread positive words regarding meat with traceability system. A number of theoretical and managerial implications as well as future study directions are offered at the end of this study report.
Keywords: Perceived usefulness, product knowledge, social norms, traceability, word-of-mouth,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1630599 Multivariate Output-Associative RVM for Multi-Dimensional Affect Predictions
Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins
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The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.Keywords: Dimensional affect prediction, Output-associative RVM, Multivariate regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1655598 A Robust Diverged Localization and Recognition of License Registration Characters
Authors: M. Sankari, R. Bremananth, C.Meena
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Localization and Recognition of License registration characters from the moving vehicle is a computationally complex task in the field of machine vision and is of substantial interest because of its diverse applications such as cross border security, law enforcement and various other intelligent transportation applications. Previous research used the plate specific details such as aspect ratio, character style, color or dimensions of the plate in the complex task of plate localization. In this paper, license registration character is localized by Enhanced Weight based density map (EWBDM) method, which is independent of such constraints. In connection with our previous method, this paper proposes a method that relaxes constraints in lighting conditions, different fonts of character occurred in the plate and plates with hand-drawn characters in various aspect quotients. The robustness of this method is well suited for applications where the appearance of plates seems to be varied widely. Experimental results show that this approach is suited for recognizing license plates in different external environments.
Keywords: Character segmentation, Connectivity checking, Edge detection, Image analysis, license plate localization, license number recognition, Quality frame selection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1876597 New Corneal Reflection Removal Method Used In Iris Recognition System
Authors: Walid Aydi, Nouri Masmoudi, Lotfi Kamoun
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Images of human iris contain specular highlights due to the reflective properties of the cornea. This corneal reflection causes many errors not only in iris and pupil center estimation but also to locate iris and pupil boundaries especially for methods that use active contour. Each iris recognition system has four steps: Segmentation, Normalization, Encoding and Matching. In order to address the corneal reflection, a novel reflection removal method is proposed in this paper. Comparative experiments of two existing methods for reflection removal method are evaluated on CASIA iris image databases V3. The experimental results reveal that the proposed algorithm provides higher performance in reflection removal.Keywords: iris, pupil, specular highlights, reflection removal
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3193596 A Novel Four-Transistor SRAM Cell with Low Dynamic Power Consumption
Authors: Arash Azizi Mazreah, Mohammad T. Manzuri Shalmani, Hamid Barati, Ali Barati
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This paper presents a novel CMOS four-transistor SRAM cell for very high density and low power embedded SRAM applications as well as for stand-alone SRAM applications. This cell retains its data with leakage current and positive feedback without refresh cycle. The new cell size is 20% smaller than a conventional six-transistor cell using same design rules. Also proposed cell uses two word-lines and one pair bit-line. Read operation perform from one side of cell, and write operation perform from another side of cell, and swing voltage reduced on word-lines thus dynamic power during read/write operation reduced. The fabrication process is fully compatible with high-performance CMOS logic technologies, because there is no need to integrate a poly-Si resistor or a TFT load. HSPICE simulation in standard 0.25μm CMOS technology confirms all results obtained from this paper.Keywords: Positive feedback, leakage current, read operation, write operation, dynamic energy consumption.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2848595 A Study of the Variability of Very Low Resolution Characters and the Feasibility of Their Discrimination Using Geometrical Features
Authors: Farshideh Einsele, Rolf Ingold
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Current OCR technology does not allow to accurately recognizing small text images, such as those found in web images. Our goal is to investigate new approaches to recognize very low resolution text images containing antialiased character shapes. This paper presents a preliminary study on the variability of such characters and the feasibility to discriminate them by using geometrical features. In a first stage we analyze the distribution of these features. In a second stage we present a study on the discriminative power for recognizing isolated characters, using various rendering methods and font properties. Finally we present interesting results of our evaluation tests leading to our conclusion and future focus.Keywords: World Wide Web, document analysis, pattern recognition, Optical Character Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1358594 Puff Noise Detection and Cancellation for Robust Speech Recognition
Authors: Sangjun Park, Jungpyo Hong, Byung-Ok Kang, Yun-keun Lee, Minsoo Hahn
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In this paper, an algorithm for detecting and attenuating puff noises frequently generated under the mobile environment is proposed. As a baseline system, puff detection system is designed based on Gaussian Mixture Model (GMM), and 39th Mel Frequency Cepstral Coefficient (MFCC) is extracted as feature parameters. To improve the detection performance, effective acoustic features for puff detection are proposed. In addition, detected puff intervals are attenuated by high-pass filtering. The speech recognition rate was measured for evaluation and confusion matrix and ROC curve are used to confirm the validity of the proposed system.Keywords: Gaussian mixture model, puff detection and cancellation, speech enhancement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2214593 Preferred Character Size for Oblique Angles
Authors: Photjanat Phimnom, Haruetai Lohasiriwat
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In today’s world, the LED display has been used for presenting visual information under various circumstances. Such information is an important intermediary in the human information processing. Researchers have been investigated diverse factors that influence this process effectiveness. The letter size is undoubtedly one major factor that has been tested and recommended by many standards and guidelines. However, viewing information on the display from direct perpendicular position is a typical assumption whereas many actual events are required viewing from the angles. This current research aims to study the effect of oblique viewing angle and viewing distance on ability to recognize alphabet, number, and English word. The total of ten participants was volunteered to our 3 x 4 x 4 within subject study. Independent variables include three distance levels (2, 6, and 12 m), four oblique angles (0, 45, 60, 75 degree), and four target types (alphabet, number, short word, and long word). Following the method of constant stimuli our study suggests that the larger oblique angle, ranging from 0 to 75 degree from the line of sight, results in significant higher legibility threshold or larger font size required (p-value < 0.05). Viewing distance factor also shows to have significant effect on the threshold (p-value < 0.05). However, the effect from distance factor is expected to be confounded by the quality of the screen used in our experiment. Lastly, our results show that single alphabet as well as single number are recognized at significant lower threshold (smaller font size) as compared to both short and long words (p-value < 0.05). Therefore, it is recommended that when designs information to be presented on LED display, understanding of all possible ranges of oblique angle should be taken into account in order to specify the preferred letter size. Additionally, the recommendation of letter size for 100% legibility in our tested conditions is provided in the paper.
Keywords: Letter Size, Oblique Angle, Viewing Distance, Legibility Threshold.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1322592 Face Localization Using Illumination-dependent Face Model for Visual Speech Recognition
Authors: Robert E. Hursig, Jane X. Zhang
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A robust still image face localization algorithm capable of operating in an unconstrained visual environment is proposed. First, construction of a robust skin classifier within a shifted HSV color space is described. Then various filtering operations are performed to better isolate face candidates and mitigate the effect of substantial non-skin regions. Finally, a novel Bhattacharyya-based face detection algorithm is used to compare candidate regions of interest with a unique illumination-dependent face model probability distribution function approximation. Experimental results show a 90% face detection success rate despite the demands of the visually noisy environment.Keywords: Audio-visual speech recognition, Bhattacharyyacoefficient, face detection,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1610591 A Survey on Facial Feature Points Detection Techniques and Approaches
Authors: Rachid Ahdid, Khaddouj Taifi, Said Safi, Bouzid Manaut
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Automatic detection of facial feature points plays an important role in applications such as facial feature tracking, human-machine interaction and face recognition. The majority of facial feature points detection methods using two-dimensional or three-dimensional data are covered in existing survey papers. In this article chosen approaches to the facial features detection have been gathered and described. This overview focuses on the class of researches exploiting facial feature points detection to represent facial surface for two-dimensional or three-dimensional face. In the conclusion, we discusses advantages and disadvantages of the presented algorithms.Keywords: Facial feature points, face recognition, facial feature tracking, two-dimensional data, three-dimensional data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1666590 Corporate Cautionary Statement: A Genre of Professional Communication
Authors: Chie Urawa
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Cautionary statements or disclaimers in corporate annual reports need to be carefully designed because clear cautionary statements may protect a company in the case of legal disputes and may undermine positive impressions. This study compares the language of cautionary statements using two corpora, Sony’s cautionary statement corpus (S-corpus) and Panasonic’s cautionary statement corpus (P-corpus), illustrating the differences and similarities in relation to the use of meaningful cautionary statements and critically analyzing why practitioners use the way. The findings describe the distinct differences between the two companies in the presentation of the risk factors and the way how they make the statements. The word ability is used more for legal protection in S-corpus whereas the word possibility is used more to convey a better impression in P-corpus. The main similarities are identified in the use of lexical words and pronouns, and almost the same wordings for eight years. The findings show how they make the statements unique to the company in the presentation of risk factors, and the characteristics of specific genre of professional communication. Important implications of this study are that more comprehensive approach can be applied in other contexts, and be used by companies to reflect upon their cautionary statements.
Keywords: Cautionary statements, corporate annual reports, corpus, risk factors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 847589 3D Star Skeleton for Fast Human Posture Representation
Authors: Sungkuk Chun, Kwangjin Hong, Keechul Jung
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In this paper, we propose an improved 3D star skeleton technique, which is a suitable skeletonization for human posture representation and reflects the 3D information of human posture. Moreover, the proposed technique is simple and then can be performed in real-time. The existing skeleton construction techniques, such as distance transformation, Voronoi diagram, and thinning, focus on the precision of skeleton information. Therefore, those techniques are not applicable to real-time posture recognition since they are computationally expensive and highly susceptible to noise of boundary. Although a 2D star skeleton was proposed to complement these problems, it also has some limitations to describe the 3D information of the posture. To represent human posture effectively, the constructed skeleton should consider the 3D information of posture. The proposed 3D star skeleton contains 3D data of human, and focuses on human action and posture recognition. Our 3D star skeleton uses the 8 projection maps which have 2D silhouette information and depth data of human surface. And the extremal points can be extracted as the features of 3D star skeleton, without searching whole boundary of object. Therefore, on execution time, our 3D star skeleton is faster than the “greedy" 3D star skeleton using the whole boundary points on the surface. Moreover, our method can offer more accurate skeleton of posture than the existing star skeleton since the 3D data for the object is concerned. Additionally, we make a codebook, a collection of representative 3D star skeletons about 7 postures, to recognize what posture of constructed skeleton is.Keywords: computer vision, gesture recognition, skeletonization, human posture representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2100588 A Low Power SRAM Base on Novel Word-Line Decoding
Authors: Arash Azizi Mazreah, Mohammad T. Manzuri Shalmani, Hamid Barati, Ali Barati, Ali Sarchami
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This paper proposes a low power SRAM based on five transistor SRAM cell. Proposed SRAM uses novel word-line decoding such that, during read/write operation, only selected cell connected to bit-line whereas, in conventional SRAM (CV-SRAM), all cells in selected row connected to their bit-lines, which in turn develops differential voltages across all bit-lines, and this makes energy consumption on unselected bit-lines. In proposed SRAM memory array divided into two halves and this causes data-line capacitance to reduce. Also proposed SRAM uses one bit-line and thus has lower bit-line leakage compared to CV-SRAM. Furthermore, the proposed SRAM incurs no area overhead, and has comparable read/write performance versus the CV-SRAM. Simulation results in standard 0.25μm CMOS technology shows in worst case proposed SRAM has 80% smaller dynamic energy consumption in each cycle compared to CV-SRAM. Besides, energy consumption in each cycle of proposed SRAM and CV-SRAM investigated analytically, the results of which are in good agreement with the simulation results.Keywords: SRAM, write Operation, read Operation, capacitances, dynamic energy consumption.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2631587 Adaptive Dynamic Time Warping for Variable Structure Pattern Recognition
Authors: S. V. Yendiyarov
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Pattern discovery from time series is of fundamental importance. Particularly, when information about the structure of a pattern is not complete, an algorithm to discover specific patterns or shapes automatically from the time series data is necessary. The dynamic time warping is a technique that allows local flexibility in aligning time series. Because of this, it is widely used in many fields such as science, medicine, industry, finance and others. However, a major problem of the dynamic time warping is that it is not able to work with structural changes of a pattern. This problem arises when the structure is influenced by noise, which is a common thing in practice for almost every application. This paper addresses this problem by means of developing a novel technique called adaptive dynamic time warping.
Keywords: Pattern recognition, optimal control, quadratic programming, dynamic programming, dynamic time warping, sintering control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2027586 GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts
Authors: Lin Cheng, Zijiang Yang
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Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.Keywords: program synthesis, flow chart, specification, graph recognition, CNN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 798585 Addressing Scalability Issues of Named Entity Recognition Using Multi-Class Support Vector Machines
Authors: Mona Soliman Habib
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This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1680584 Finding an Optimized Discriminate Function for Internet Application Recognition
Authors: E. Khorram, S.M. Mirzababaei
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Everyday the usages of the Internet increase and simply a world of the data become accessible. Network providers do not want to let the provided services to be used in harmful or terrorist affairs, so they used a variety of methods to protect the special regions from the harmful data. One of the most important methods is supposed to be the firewall. Firewall stops the transfer of such packets through several ways, but in some cases they do not use firewall because of its blind packet stopping, high process power needed and expensive prices. Here we have proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. So an administrator can alarm to the user. This method is very fast and can be used simply in adjacent with the Internet routers.
Keywords: Data Mining, Firewall, Optimization, Packetclassification, Statistical Pattern Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1396583 Automatic Fingerprint Classification Using Graph Theory
Authors: Mana Tarjoman, Shaghayegh Zarei
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Using efficient classification methods is necessary for automatic fingerprint recognition system. This paper introduces a new structural approach to fingerprint classification by using the directional image of fingerprints to increase the number of subclasses. In this method, the directional image of fingerprints is segmented into regions consisting of pixels with the same direction. Afterwards the relational graph to the segmented image is constructed and according to it, the super graph including prominent information of this graph is formed. Ultimately we apply a matching technique to compare obtained graph with the model graphs in order to classify fingerprints by using cost function. Increasing the number of subclasses with acceptable accuracy in classification and faster processing in fingerprints recognition, makes this system superior.
Keywords: Classification, Directional image, Fingerprint, Graph, Super graph.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3611582 Bio-Inspired Generalized Global Shape Approach for Writer Identification
Authors: Azah Kamilah Muda, Siti Mariyam Shamsuddin, Maslina Darus
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Writer identification is one of the areas in pattern recognition that attract many researchers to work in, particularly in forensic and biometric application, where the writing style can be used as biometric features for authenticating an identity. The challenging task in writer identification is the extraction of unique features, in which the individualistic of such handwriting styles can be adopted into bio-inspired generalized global shape for writer identification. In this paper, the feasibility of generalized global shape concept of complimentary binding in Artificial Immune System (AIS) for writer identification is explored. An experiment based on the proposed framework has been conducted to proof the validity and feasibility of the proposed approach for off-line writer identification.Keywords: Writer identification, generalized global shape, individualistic, pattern recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1215581 Effective Traffic Lights Recognition Method for Real Time Driving Assistance Systemin the Daytime
Authors: Hyun-Koo Kim, Ju H. Park, Ho-Youl Jung
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This paper presents an effective traffic lights recognition method at the daytime. First, Potential Traffic Lights Detector (PTLD) use whole color source of YCbCr channel image and make each binary image of green and red traffic lights. After PTLD step, Shape Filter (SF) use to remove noise such as traffic sign, street tree, vehicle, and building. At this time, noise removal properties consist of information of blobs of binary image; length, area, area of boundary box, etc. Finally, after an intermediate association step witch goal is to define relevant candidates region from the previously detected traffic lights, Adaptive Multi-class Classifier (AMC) is executed. The classification method uses Haar-like feature and Adaboost algorithm. For simulation, we are implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM and tested in the urban and rural roads. Through the test, we are compared with our method and standard object-recognition learning processes and proved that it reached up to 94 % of detection rate which is better than the results achieved with cascade classifiers. Computation time of our proposed method is 15 ms.Keywords: Traffic Light Detection, Multi-class Classification, Driving Assistance System, Haar-like Feature, Color SegmentationMethod, Shape Filter
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2768580 Holistic Face Recognition using Multivariate Approximation, Genetic Algorithms and AdaBoost Classifier: Preliminary Results
Authors: C. Villegas-Quezada, J. Climent
Abstract:
Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.
Keywords: AdaBoost Classifier, Holistic Face Recognition, Minimax Multivariate Approximation, Genetic Algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1481579 Visual Object Tracking and Interception in Industrial Settings
Authors: Ahmet Denker, Tuğrul Adıgüzel
Abstract:
This paper presents a solution for a robotic manipulation problem. We formulate the problem as combining target identification, tracking and interception. The task in our solution is sensing a target on a conveyor belt and then intercepting robot-s end-effector at a convenient rendezvous point. We used an object recognition method which identifies the target and finds its position from visualized scene picture, then the robot system generates a solution for rendezvous problem using the target-s initial position and belt velocity . The interception of the target and the end-effector is executed at a convenient rendezvous point along the target-s calculated trajectory. Experimental results are obtained using a real platform with an industrial robot and a vision system over it.Keywords: Object recognition, rendezvous planning, robotics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1712