Search results for: visual thing recognition system

Authors: Jana Teplá

Abstract:

This text focuses on the visual construction of youth in press photographs in socialist Czechoslovakia. It deals with photographs in a magazine for young readers, Mladý svět, published by the Socialist Union of Youth of Czechoslovakia. The aim of this study was to develop a methodological tool for uncovering the values and the ideological messages in the strategies used in the visual construction of reality in the socialist press. Two methods of visual analysis were applied to the photographs, a quantitative content analysis and a social semiotic analysis. The social semiotic analysis focused on images representing youth in their free time. The study shows that the meaning of a socialist press photograph is a result of a struggle for ideological power between formal and informal ideologies. This struggle takes place within the process of production of the photograph and also within the process of interpretation of the photograph.

Keywords: Ideology, press photography, socialist regime, social semiotics, youth.

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Authors: Abdallah M. Abualkishik, Khairuddin Omar

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This article concerned with the translation of Quranic verses to Braille symbols, by using Visual basic program. The system has the ability to translate the special vibration for the Quran. This study limited for the (Noun + Scoon) vibrations. It builds on an existing translation system that combines a finite state machine with left and right context matching and a set of translation rules. This allows to translate the Arabic language from text to Braille symbols after detect the vibration for the Quran verses.

Keywords: Braille, Quran vibration, Finite State Machine.

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Authors: Wernhuar Tarng, Yuan-Yuan Chen, Chien-Lung Li, Kun-Rong Hsie, Mingteh Chen

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An emotional speech recognition system for the applications on smart phones was proposed in this study to combine with 3G mobile communications and social networks to provide users and their groups with more interaction and care. This study developed a mechanism using the support vector machines (SVM) to recognize the emotions of speech such as happiness, anger, sadness and normal. The mechanism uses a hierarchical classifier to adjust the weights of acoustic features and divides various parameters into the categories of energy and frequency for training. In this study, 28 commonly used acoustic features including pitch and volume were proposed for training. In addition, a time-frequency parameter obtained by continuous wavelet transforms was also used to identify the accent and intonation in a sentence during the recognition process. The Berlin Database of Emotional Speech was used by dividing the speech into male and female data sets for training. According to the experimental results, the accuracies of male and female test sets were increased by 4.6% and 5.2% respectively after using the time-frequency parameter for classifying happy and angry emotions. For the classification of all emotions, the average accuracy, including male and female data, was 63.5% for the test set and 90.9% for the whole data set.

Keywords: Smart phones, emotional speech recognition, socialnetworks, support vector machines, time-frequency parameter, Mel-scale frequency cepstral coefficients (MFCC).

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Authors: Jie Zhao, Meng Su

Abstract:

Image recognition enables machine-like robotics to understand a scene and plays an important role in computer vision applications. Computer vision platforms as physical infrastructure, supporting Neural Networks for image recognition, are deterministic to leverage the performance of different Neural Networks. In this paper, three different computer vision platforms – edge AI (Jetson Nano, with 4GB), a standalone laptop (with RTX 3000s, using CUDA), and a web-based device (Google Colab, using GPU) are investigated. In the case study, four prominent neural network architectures (including AlexNet, VGG16, GoogleNet, and ResNet (34/50)), are deployed. By using public ImageNets (Cifar-10), our findings provide a nuanced perspective on optimizing image recognition tasks across Edge-AI platforms, offering guidance on selecting appropriate neural network structures to maximize performance under hardware constraints.

Keywords: AlexNet, VGG, GoogleNet, ResNet, ImageNet, Cifar-10, Edge AI, Jetson Nano, CUDA, GPU.

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Authors: Zaheer Ahmad, Jehanzeb Khan Orakzai, Inam Shamsher, Awais Adnan

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This paper discusses the Urdu script characteristics, Urdu Nastaleeq and a simple but a novel and robust technique to recognize the printed Urdu script without a lexicon. Urdu being a family of Arabic script is cursive and complex script in its nature, the main complexity of Urdu compound/connected text is not its connections but the forms/shapes the characters change when it is placed at initial, middle or at the end of a word. The characters recognition technique presented here is using the inherited complexity of Urdu script to solve the problem. A word is scanned and analyzed for the level of its complexity, the point where the level of complexity changes is marked for a character, segmented and feeded to Neural Networks. A prototype of the system has been tested on Urdu text and currently achieves 93.4% accuracy on the average.

Keywords: Cursive Script, OCR, Urdu.

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Authors: Chapman Eze Nnadozie

Abstract:

Relational databases constitute a very vital tool for the effective management and administration of both personal and organizational data. Data access ranges from a single user database management software to a more complex distributed server system. This paper intends to appraise the use a programming language extension like structured query language (SQL) to establish links to a relational database (Microsoft Access 2013) using Visual C++ 9 programming language environment. The methodology used involves the creation of tables to form a database using Microsoft Access 2013, which is Object Linking and Embedding (OLE) database compliant. The SQL command is used to query the tables in the database for easy extraction of expected records inside the visual C++ environment. The findings of this paper reveal that records can easily be accessed and manipulated to filter exactly what the user wants, such as retrieval of records with specified criteria, updating of records, and deletion of part or the whole records in a table.

Keywords: Data access, database, database management system, OLE, programming language, records, relational database, software, SQL, table.

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Authors: T. Arudchelvam, W. W. E. N. Fernando

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Mobile phone has become as an essential thing in our life. Therefore, security is the most important thing to be considered in mobile communication. Short message service is the cheapest way of communication via the mobile phones. Therefore, security is very important in the short message service as well. This paper presents a method to maintain the security at user level. Different types of encryption methods are used to implement the user level security in mobile phones. Caesar cipher, Rail Fence, Vigenere cipher and RSA are used as encryption methods in this work. Caesar cipher and the Rail Fence methods are enhanced and implemented. The beauty in this work is that the user can select the encryption method and the key. Therefore, by changing the encryption method and the key time to time, the user can ensure the security of messages. By this work, while users can safely send/receive messages, they can save their information from unauthorised and unwanted people in their own mobile phone as well.

Keywords: SMS, user level security, encryption, mobile communication.

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Authors: Ayşe Nihan Avcı, İpek Memikoğlu

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Lighting systems in interior architecture need to be designed according to the function of the space, the type of task within the space, user comfort and needs. Desired and comfortable lighting levels increase task efficiency. When natural lighting is inadequate in a space, artificial lighting is additionally used to support the level of light. With the technological developments, the characteristics of light are being researched comprehensively and several business segments have focused on its qualitative and quantitative characteristics. These studies have increased awareness and usage of artificial lighting systems and researchers have investigated the effects of lighting on physical and psychological aspects of human in various ways. The aim of this study is to research the effects of illuminance levels of LED lighting on user visual comfort. Eighty participants from the Department of Interior Architecture of Çankaya University participated in three lighting scenarios consisting of 200 lux, 500 lux and 800 lux that are created with LED lighting. Each lighting scenario is evaluated according to six visual comfort criteria in which a reading task is performed. The results of the study indicated that LED lighting with three different illuminance levels affect visual comfort in different ways. The results are limited to the participants and questions that are attended and used in this study.

Keywords: Illuminance levels, LED lighting, reading task, visual comfort criteria.

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Authors: H. W. Ker

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Longitudinal data typically have the characteristics of changes over time, nonlinear growth patterns, between-subjects variability, and the within errors exhibiting heteroscedasticity and dependence. The data exploration is more complicated than that of cross-sectional data. The purpose of this paper is to organize/integrate of various visual-graphical techniques to explore longitudinal data. From the application of the proposed methods, investigators can answer the research questions include characterizing or describing the growth patterns at both group and individual level, identifying the time points where important changes occur and unusual subjects, selecting suitable statistical models, and suggesting possible within-error variance.

Keywords: Data exploration, exploratory analysis, HLMs/LMEs, longitudinal data, visual-graphical methods.

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Authors: Angela Ralli, Eleni Galiotou

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In this paper we describe the recognition process of Greek compound words using the PC-KIMMO software. We try to show certain limitations of the system with respect to the principles of compound formation in Greek. Moreover, we discuss the computational processing of phenomena such as stress and syllabification which are indispensable for the analysis of such constructions and we try to propose linguistically-acceptable solutions within the particular system.

Keywords: Morpho-phonological parsing, compound words, two-level morphology, natural language processing.

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Prateek Gupta

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The current research paper is an implementation of Eigen Faces and Karhunen-Loeve Algorithm for face recognition. The designed program works in a manner where a unique identification number is given to each face under trial. These faces are kept in a database from where any particular face can be matched and found out of the available test faces. The Karhunen –Loeve Algorithm has been implemented to find out the appropriate right face (with same features) with respect to given input image as test data image having unique identification number. The procedure involves usage of Eigen faces for the recognition of faces.

Keywords: Eigen Faces, Karhunen-Loeve Algorithm, FaceRecognition.

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Authors: Pengfei Xiong, Lei Huang, Changping Liu

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In illumination variant face recognition, existing methods extracting face albedo as light normalized image may lead to loss of extensive facial details, with light template discarded. To improve that, a novel approach for realistic facial texture reconstruction by combining original image and albedo image is proposed. First, light subspaces of different identities are established from the given reference face images; then by projecting the original and albedo image into each light subspace respectively, texture reference images with corresponding lighting are reconstructed and two texture subspaces are formed. According to the projections in texture subspaces, facial texture with normal light can be synthesized. Due to the combination of original image, facial details can be preserved with face albedo. In addition, image partition is applied to improve the synthesization performance. Experiments on Yale B and CMUPIE databases demonstrate that this algorithm outperforms the others both in image representation and in face recognition.

Keywords: texture reconstruction, illumination, face recognition, subspaces

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Authors: Matko Šaric, Hrvoje Dujmic, Vladan Papic, Nikola Rožic

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Detection of player identity is challenging task in sport video content analysis. In case of soccer video player number recognition is effective and precise solution. Jersey numbers can be considered as scene text and difficulties in localization and recognition appear due to variations in orientation, size, illumination, motion etc. This paper proposed new method for player number localization and recognition. By observing hue, saturation and value for 50 different jersey examples we noticed that most often combination of low and high saturated pixels is used to separate number and jersey region. Image segmentation method based on this observation is introduced. Then, novel method for player number localization based on internal contours is proposed. False number candidates are filtered using area and aspect ratio. Before OCR processing extracted numbers are enhanced using image smoothing and rotation normalization.

Keywords: player number, soccer video, HSV color space

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Authors: Hunny Mehrotra, Banshidhar Majhi, Phalguni Gupta

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The paper proposes a novel technique for iris recognition using texture and phase features. Texture features are extracted on the normalized iris strip using Haar Wavelet while phase features are obtained using LOG Gabor Wavelet. The matching scores generated from individual modules are combined using sum of score technique. The system is tested on database obtained from Bath University and Indian Institute of Technology Kanpur and is giving an accuracy of 95.62% and 97.66% respectively. The FAR and FRR of the combined system is also reduced comparatively.

Keywords: Fusion, Haar Wavelet, Iris, LOG Gabor Wavelet, Phase, Texture.

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Authors: Giovanni Luca Masala

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Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Keywords: Computer Aided Detection, mammary tumor, pattern recognition, thalassemia.

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: Classification, fuzzy, inspection system, image analysis.

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Authors: Soo- Young Ye, Dong-Hyun Kim

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Obstructive sleep apnea in patients, between 70 and 80 percent, can be cured with just a posture correcting. The most import thing to do this is detection of obstructive sleep apnea. Detection of obstructive sleep apnea can be performed through heart rate variability analysis using power spectrum density analysis. After HRV analysis we needed to know the current position information for correcting the position. The pressure sensors of the array type were used to obtain position information. These sensors can obtain information from the experimenter about position. In addition, air cylinder corrected the position of the experimenter by lifting the bed. The experimenter can be changed position without breaking during sleep by the system. Polysomnograph recording were obtained from 10 patients. The results of HRV analysis were that NLF and LF/HF ratio increased, while NHF decreased during OSA. Position change had to be done the periods.

Keywords: Obstructive sleep apnea, Heart rate variability, Air cylinder, PSD, RR interval, ANS

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Authors: Rami N. Khushaba, Adel Al-Jumaily

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The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.

Keywords: Biomedical Signal Processing, Data mining andInformation Extraction, Machine Learning, Rehabilitation.

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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.

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Authors: Anastasis Kounoudes, Stephanos Mavromoustakos

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Electronic commerce is growing rapidly with on-line sales already heading for hundreds of billion dollars per year. Due to the huge amount of money transferred everyday, an increased security level is required. In this work we present the architecture of an intelligent speaker verification system, which is able to accurately verify the registered users of an e-commerce service using only their voices as an input. According to the proposed architecture, a transaction-based e-commerce application should be complemented by a biometric server where customer-s unique set of speech models (voiceprint) is stored. The verification procedure requests from the user to pronounce a personalized sequence of digits and after capturing speech and extracting voice features at the client side are sent back to the biometric server. The biometric server uses pattern recognition to decide whether the received features match the stored voiceprint of the customer who claims to be, and accordingly grants verification. The proposed architecture can provide e-commerce applications with a higher degree of certainty regarding the identity of a customer, and prevent impostors to execute fraudulent transactions.

Keywords: Speaker Recognition, Biometrics, E-commercesecurity.

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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.

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Authors: S. Ntalampiras, I. Potamitis, N. Fakotakis, S. Kouzoupis

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The present work faces the problem of automatic enumeration and recognition of an unknown and time-varying number of environmental sound sources while using a single microphone. The assumption that is made is that the sound recorded is a realization of sound sources belonging to a group of audio classes which is known a-priori. We describe two variations of the same principle which is to calculate the distance between the current unknown audio frame and all possible combinations of the classes that are assumed to span the soundscene. We concentrate on categorizing environmental sound sources, such as birds, insects etc. in the task of monitoring the biodiversity of a specific habitat.

Keywords: automatic recognition of multiple sound sources, enumeration of sound sources, computational ecology.

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Authors: Awais Adnan, Muhammad Ali, Amir Hanif Dar

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Image Searching was always a problem specially when these images are not properly managed or these are distributed over different locations. Currently different techniques are used for image search. On one end, more features of the image are captured and stored to get better results. Storing and management of such features is itself a time consuming job. While on the other extreme if fewer features are stored the accuracy rate is not satisfactory. Same image stored with different visual properties can further reduce the rate of accuracy. In this paper we present a new concept of using polynomials of sorted histogram of the image. This approach need less overhead and can cope with the difference in visual features of image.

Keywords: Sorted Histogram, Polynomial Curves, feature pointsof images, Grayscale, visual properties of image.

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Authors: Marcell S. A. Martins, Benedito S. R. Neto, Gerson L. Serejo, Carlos G. R. Santos

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Indoor positioning systems use sensors such as Bluetooth, ZigBee, and Wi-Fi, as well as cameras for image capture, which can be fixed or mobile. These computer vision-based positioning approaches are low-cost to implement, mainly when it uses a mobile camera. The present study aims to create a design of a fiducial marker for a low-cost indoor localization system. The marker is tape-shaped to perform a continuous reading employing two detection algorithms, one for greater distances and another for smaller distances. Therefore, the location service is always operational, even with variations in capture distance. A minimal localization and reading algorithm was implemented for the proposed marker design, aiming to validate it. The accuracy tests consider readings varying the capture distance between [0.5, 10] meters, comparing the proposed marker with others. The tests showed that the proposed marker has a broader capture range than the ArUco and QRCode, maintaining the same size. Therefore, reducing the visual pollution and maximizing the tracking since the ambient can be covered entirely.

Keywords: Multiscale recognition, indoor localization, tape-shaped marker, Fiducial Marker.

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Authors: S. Porojan, L. Sandu, F. Topalâ

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Microplasma welding is a less expensive alternative to laser welding in dental technology. The aim of the study was to highlight discontinuities present in the microplasma welded joints of dental base metal alloys by visual analysis. Five base metal alloys designated for fixed prostheses manufacture were selected for the experiments. Using these plates, preliminary tests were conducted by microplasma welding in butt joint configuration, without filler material, bilaterally and with filler material, proper for each base metal. Macroscopic visual inspection was performed to assess carefully the irregularities in the welds. Electron microscopy allowed detection of discontinuities that are not visible to the eye and revealing details regarding location, trajectory, morphology and size of discontinuities. Supplementing visual control with microscopic analysis allows to detect small discontinuities, which escapes the macroscopic control and to make a detailed study of the weld.

Keywords: base metal alloys, fixed prosthodontics, microplasmawelding, visual inspection

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Authors: Bia Kim, Sewon Lee, Jaesik Lee

Abstract:

This study aims to investigate the gender differences in spatial navigation using the tasks of 2-D matrix navigation and recognition of real driving scene. The results can be summarized as followings. First, female subjects responded faster in 2-D matrix navigation task than male subjects when landmark instructions were provided. Second, in recognition task, male subjects recognized the key elements involved in the past driving scene more accurately than female subjects. In particular, female subjects tended to miss peripheral information. These results suggest the possibility of gender differences in spatial navigation.

Keywords: Gender differences, Spatial navigation, 2-D matrixnavigation, Recognition of driving scene.

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Authors: Sanmohan Krüger, Volker Krüger

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Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper an online algorithm to recognize parametric actions with object context is presented. Objects are key instruments in understanding an action when there is uncertainty. Ambiguities arising in similar actions can be resolved with objectn context. We classify actions according to the changes they make to the object space. Actions that produce the same state change in the object movement space are classified to belong to the same class. This allow us to define several classes of actions where members of each class are connected with a semantic interpretation.

Keywords: Parametric actions, Action primitives, Hand gesture recognition, Imitation learning

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Authors: Xiang Zhang, Daohong Yang, Ziyuan Wu, Lei Li, Wanting Zhou

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Visual Simultaneous Localization and Mapping (VSLAM) uses cameras to gather information in unknown environments to achieve simultaneous localization and mapping of the environment. This technology has a wide range of applications in autonomous driving, virtual reality, and other related fields. Currently, the research advancements related to VSLAM can maintain high accuracy in static environments. But in dynamic environments, the presence of moving objects in the scene can reduce the stability of the VSLAM system, leading to inaccurate localization and mapping, or even system failure. In this paper, a robust VSLAM method was proposed to effectively address the challenges in dynamic environments. We proposed a dynamic region removal scheme based on a semantic segmentation neural network and geometric constraints. Firstly, a semantic segmentation neural network is used to extract the prior active motion region, prior static region, and prior passive motion region in the environment. Then, the lightweight frame tracking module initializes the transform pose between the previous frame and the current frame on the prior static region. A motion consistency detection module based on multi-view geometry and scene flow is used to divide the environment into static regions and dynamic regions. Thus, the dynamic object region was successfully eliminated. Finally, only the static region is used for tracking thread. Our research is based on the ORBSLAM3 system, which is one of the most effective VSLAM systems available. We evaluated our method on the TUM RGB-D benchmark and the results demonstrate that the proposed VSLAM method improves the accuracy of the original ORBSLAM3 by 70%˜98.5% under a high dynamic environment.

Keywords: Dynamic scene, dynamic visual SLAM, semantic segmentation, scene flow, VSLAM.

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Authors: Tadatsugu Kitamoto

Abstract:

Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system.

Keywords: Acoustical diagnosis, Neural networks, K-means, Short-time Fourier transformation

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Authors: Jawad H AlKhateeb, Jianmin Jiang, Jinchang Ren, Stan S Ipson

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Efficient preprocessing is very essential for automatic recognition of handwritten documents. In this paper, techniques on segmenting words in handwritten Arabic text are presented. Firstly, connected components (ccs) are extracted, and distances among different components are analyzed. The statistical distribution of this distance is then obtained to determine an optimal threshold for words segmentation. Meanwhile, an improved projection based method is also employed for baseline detection. The proposed method has been successfully tested on IFN/ENIT database consisting of 26459 Arabic words handwritten by 411 different writers, and the results were promising and very encouraging in more accurate detection of the baseline and segmentation of words for further recognition.

Keywords: Arabic OCR, off-line recognition, Baseline estimation, Word segmentation.

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