Abstract Word is the preferred and natural unit of speech, because word units have well defined acoustic representation. This paper presents several dynamic thresholding approaches for segmenting continuous Bangla speech sentences into words/sub-words. We have proposed three efficient methods for speech segmentation: two of them are usually used in pattern classification (i.e., k-means and FCM clustering) and one of them is used in image segmentation (i.e., Otsu’s thresholding method). We also used new approaches blocking black area and boundary detection techniques to properly detect word boundaries in continuous speech and label the entire speech sentence into a sequence of words/sub-words. K-Means and FCM clustering methods produce better segmentation results than that of Otsu’s Method. All the algorithms and methods used in this research are implemented in MATLAB and the proposed system achieved the average segmentation accuracy of 94% approximately. Keywords: Blocking Black Area, Clustering, Dynamic Thresholding, Fuzzy Logic and Speech Segmentation.
Inpainting scheme for text in video a surveyeSAT Journals
Abstract
Text data present in video sequences provide useful information of paramount requirement. Although text present in video provide
useful information not all are of them are necessary because it may hide the important portion of the video. So there must way to
erase this type of unwanted text. This can be done in two phase first text components are detected from each frame of the video.
Detected text component are then removed from the video sequences. And restore the occluded part of the video using inpaint
method. This text detection and removal scheme is in two phases. Each phase is broad topic of image processing. Video text
detection and Inpainting are two most important phase in this scheme. Text detection phase consist of text localization, text
segmentation and recognition phase. Inpainting method is used for restoring occluded part produce due to removal of text.
Keywords—Optical Character Recognition(OCR), Stroke width transform, Text Detection,Connected Component
Segmentation and recognition of handwritten digit numeral string using a mult...ijfcstjournal
In this paper, the use of Multi-Layer Perceptron (MLP) Neural Network model is proposed for recognizing
unconstrained offline handwritten Numeral strings. The Numeral strings are segmented and isolated
numerals are obtained using a connected component labeling (CCL) algorithm approach. The structural
part of the models has been modeled using a Multilayer Perceptron Neural Network. This paper also
presents a new technique to remove slope and slant from handwritten numeral string and to normalize the
size of text images and classify with supervised learning methods. Experimental results on a database of
102 numeral string patterns written by 3 different people show that a recognition rate of 99.7% is obtained
on independent digits contained in the numeral string of digits includes both the skewed and slant data.
Software projects mostly exceeds budget, delivered late and does not meet with the customer’s satisfaction for years. In the past, many traditional development models like waterfall, spiral, iterative, and prototyping methods are used to build the software systems. In recent years, agile models are widely used in developing the software products. The major reasons are – simplicity, incorporating the requirement changes at any time, light-weight approach and delivering the working product early and in short duration. Whatever the development model used, it still remains a challenge for software engineer’s to accurately estimate the size, effort and the time required for developing the software system. This survey focuses on the existing estimation models used in traditional as well in agile software development.
DETECTION OF CONCEALED WEAPONS IN X-RAY IMAGES USING FUZZY K-NNIJCSEIT Journal
Scanning baggage by x-ray and analysing such images have become important technique for detecting
illicit materials in the baggage at Airports. In order to provide adequate security, a reliable and fast
screening technique is needed for baggage examination.This paper aims at providing an automatic method
for detecting concealed weapons, typically a gun in the baggage by employing image segmentation method
to extract the objects of interest from the image followed by applying feature extraction methods namely
Shape context descriptor and Zernike moments. Finally the objects are classified using fuzzy KNN as illicit
or non-illicit object.
Inpainting scheme for text in video a surveyeSAT Journals
Abstract
Text data present in video sequences provide useful information of paramount requirement. Although text present in video provide
useful information not all are of them are necessary because it may hide the important portion of the video. So there must way to
erase this type of unwanted text. This can be done in two phase first text components are detected from each frame of the video.
Detected text component are then removed from the video sequences. And restore the occluded part of the video using inpaint
method. This text detection and removal scheme is in two phases. Each phase is broad topic of image processing. Video text
detection and Inpainting are two most important phase in this scheme. Text detection phase consist of text localization, text
segmentation and recognition phase. Inpainting method is used for restoring occluded part produce due to removal of text.
Keywords—Optical Character Recognition(OCR), Stroke width transform, Text Detection,Connected Component
Segmentation and recognition of handwritten digit numeral string using a mult...ijfcstjournal
In this paper, the use of Multi-Layer Perceptron (MLP) Neural Network model is proposed for recognizing
unconstrained offline handwritten Numeral strings. The Numeral strings are segmented and isolated
numerals are obtained using a connected component labeling (CCL) algorithm approach. The structural
part of the models has been modeled using a Multilayer Perceptron Neural Network. This paper also
presents a new technique to remove slope and slant from handwritten numeral string and to normalize the
size of text images and classify with supervised learning methods. Experimental results on a database of
102 numeral string patterns written by 3 different people show that a recognition rate of 99.7% is obtained
on independent digits contained in the numeral string of digits includes both the skewed and slant data.
Software projects mostly exceeds budget, delivered late and does not meet with the customer’s satisfaction for years. In the past, many traditional development models like waterfall, spiral, iterative, and prototyping methods are used to build the software systems. In recent years, agile models are widely used in developing the software products. The major reasons are – simplicity, incorporating the requirement changes at any time, light-weight approach and delivering the working product early and in short duration. Whatever the development model used, it still remains a challenge for software engineer’s to accurately estimate the size, effort and the time required for developing the software system. This survey focuses on the existing estimation models used in traditional as well in agile software development.
DETECTION OF CONCEALED WEAPONS IN X-RAY IMAGES USING FUZZY K-NNIJCSEIT Journal
Scanning baggage by x-ray and analysing such images have become important technique for detecting
illicit materials in the baggage at Airports. In order to provide adequate security, a reliable and fast
screening technique is needed for baggage examination.This paper aims at providing an automatic method
for detecting concealed weapons, typically a gun in the baggage by employing image segmentation method
to extract the objects of interest from the image followed by applying feature extraction methods namely
Shape context descriptor and Zernike moments. Finally the objects are classified using fuzzy KNN as illicit
or non-illicit object.
Multi fractal analysis of human brain mr imageeSAT Journals
Abstract In computer programming, code smell may origin of latent problems in source code. Detecting and resolving bad smells remain time intense for software engineers despite proposals on bad smell detecting and refactoring tools. Numerous code smells have been recognized yet the sequence in which the detection and resolution of different kinds of code smells are performed because software engineers do not know how to optimize sequence. In this paper, the novel refactoring approach is proposed to improve the performance of programs. In this recommended approach the code smells are automatically detected and refactored. The simulation results propose the reduction of time over the semi-automated refactoring are achieved when code smells are refactored by using multi-step automated refactoring. Keywords: Code smell, multi step refactoring, detection, code resolution, restructuring etc
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Mixed Language Based Offline Handwritten Character Recognition Using First St...CSCJournals
Artificial Neural Network is an artificial representation of the human brain that tries to simulate its learning process. To train a network and measure how well it performs, an objective function must be defined. A commonly used performance criterion function is the sum of squares error function. Full end-to-end text recognition in natural images is a challenging problem that has recently received much attention in computer vision and machine learning. Traditional systems in this area have relied on elaborate models that incorporate carefully hand-engineered features or large amounts of prior knowledge. Language identification and interpretation of handwritten characters is one of the challenges faced in various industries. For example, it is always a big challenge in data interpretation from cheques in banks, language identification and translated messages from ancient script in the form of manuscripts, palm scripts and stone carvings to name a few. Handwritten character recognition using Soft computing methods like Neural networks is always a big area of research for long time and there are multiple theories and algorithms developed in the area of neural networks for handwritten character recognition.
ROBUST TEXT DETECTION AND EXTRACTION IN NATURAL SCENE IMAGES USING CONDITIONA...ijiert bestjournal
In Natural Scene Image,Text detection is important tasks which are used for many content based image analysis. A maximally stable external region based method is us ed for scene detection .This MSER based method incl udes stages character candidate extraction,text candida te construction,text candidate elimination & text candidate classification. Main limitations of this method are how to detect highly blurred text in low resolutio n natural scene images. The current technology not focuses on any t ext extraction method. In proposed system a Conditi onal Random field (CRF) model is used to assign candidat e component as one of the two classes (text& Non Te xt) by Considering both unary component properties and bin ary contextual component relationship. For this pur pose we are using connected component analysis method. The proposed system also performs a text extraction usi ng OCR
Representation and recognition of handwirten digits using deformable templatesAhmed Abd-Elwasaa
Representation and recognition of handwrittendigits using deformable templates, This working prototype system can detect handwritten digits from a scanned image of an input form by using deformable templates technique.
The paper is based on feed forward neural network (FFNN) optimization by particle swarm intelligence (PSI) used to provide initial weights and biases to train neural network. Once the weights and biases are found using Particle swarm optimization (PSO) with neural network used as training algorithm for specified epoch, the same are used to train the neural network for training and classification of benchmark problems. Further the approach is tested for offline signature classifications. A comparison is made between normal FFNN with random weights and biases and FFNN with particle swarm optimized weights and biases. Firstly, the performance is tested on two benchmark databases for neural network, The Breast Cancer Database and the Diabetic Database. Result shows that neural network performs better with initial weights and biases obtained by Particle Swarm optimization. The network converges faster with PSO obtained initial weights and biases for FFNN and classification accuracy is increased.
Texture features based text extraction from images using DWT and K-means clus...Divya Gera
Text extraction from different kind of images document, caption and scene text images. Discret wavelet transform was used to exract horizontal, vertical and diagonal features and k-means clustering was used to cluster the features into text and background cluster. For simple images k = 2 worked i.e. text and backgroud cluster while for complex images k=3 was used i.e. text cluster, complex background ad simple background.
A Parallel Framework For Multilayer Perceptron For Human Face RecognitionCSCJournals
Artificial neural networks have already shown their success in face recognition and similar complex pattern recognition tasks. However, a major disadvantage of the technique is that it is extremely slow during training for larger classes and hence not suitable for real-time complex problems such as pattern recognition. This is an attempt to develop a parallel framework for the training algorithm of a perceptron. In this paper, two general architectures for a Multilayer Perceptron (MLP) have been demonstrated. The first architecture is All-Class-in-One-Network (ACON) where all the classes are placed in a single network and the second one is One-Class-in-One-Network (OCON) where an individual single network is responsible for each and every class. Capabilities of these two architectures were compared and verified in solving human face recognition, which is a complex pattern recognition task where several factors affect the recognition performance like pose variations, facial expression changes, occlusions, and most importantly illumination changes. Experimental results show that the proposed OCON structure performs better than the conventional ACON in terms of network training convergence speed and which can be easily exercised in a parallel environment.
Sparse representation based classification of mr images of brain for alzheime...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A lightweight secure scheme for detecting provenance forgery and packet drop ...LeMeniz Infotech
A lightweight secure scheme for detecting provenance forgery and packet drop attacks in wireless sensor networks
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Visit : www.lemenizinfotech.com / www.ieeemaster.com
Mail : projects@lemenizinfotech.com
Multi fractal analysis of human brain mr imageeSAT Journals
Abstract In computer programming, code smell may origin of latent problems in source code. Detecting and resolving bad smells remain time intense for software engineers despite proposals on bad smell detecting and refactoring tools. Numerous code smells have been recognized yet the sequence in which the detection and resolution of different kinds of code smells are performed because software engineers do not know how to optimize sequence. In this paper, the novel refactoring approach is proposed to improve the performance of programs. In this recommended approach the code smells are automatically detected and refactored. The simulation results propose the reduction of time over the semi-automated refactoring are achieved when code smells are refactored by using multi-step automated refactoring. Keywords: Code smell, multi step refactoring, detection, code resolution, restructuring etc
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Mixed Language Based Offline Handwritten Character Recognition Using First St...CSCJournals
Artificial Neural Network is an artificial representation of the human brain that tries to simulate its learning process. To train a network and measure how well it performs, an objective function must be defined. A commonly used performance criterion function is the sum of squares error function. Full end-to-end text recognition in natural images is a challenging problem that has recently received much attention in computer vision and machine learning. Traditional systems in this area have relied on elaborate models that incorporate carefully hand-engineered features or large amounts of prior knowledge. Language identification and interpretation of handwritten characters is one of the challenges faced in various industries. For example, it is always a big challenge in data interpretation from cheques in banks, language identification and translated messages from ancient script in the form of manuscripts, palm scripts and stone carvings to name a few. Handwritten character recognition using Soft computing methods like Neural networks is always a big area of research for long time and there are multiple theories and algorithms developed in the area of neural networks for handwritten character recognition.
ROBUST TEXT DETECTION AND EXTRACTION IN NATURAL SCENE IMAGES USING CONDITIONA...ijiert bestjournal
In Natural Scene Image,Text detection is important tasks which are used for many content based image analysis. A maximally stable external region based method is us ed for scene detection .This MSER based method incl udes stages character candidate extraction,text candida te construction,text candidate elimination & text candidate classification. Main limitations of this method are how to detect highly blurred text in low resolutio n natural scene images. The current technology not focuses on any t ext extraction method. In proposed system a Conditi onal Random field (CRF) model is used to assign candidat e component as one of the two classes (text& Non Te xt) by Considering both unary component properties and bin ary contextual component relationship. For this pur pose we are using connected component analysis method. The proposed system also performs a text extraction usi ng OCR
Representation and recognition of handwirten digits using deformable templatesAhmed Abd-Elwasaa
Representation and recognition of handwrittendigits using deformable templates, This working prototype system can detect handwritten digits from a scanned image of an input form by using deformable templates technique.
The paper is based on feed forward neural network (FFNN) optimization by particle swarm intelligence (PSI) used to provide initial weights and biases to train neural network. Once the weights and biases are found using Particle swarm optimization (PSO) with neural network used as training algorithm for specified epoch, the same are used to train the neural network for training and classification of benchmark problems. Further the approach is tested for offline signature classifications. A comparison is made between normal FFNN with random weights and biases and FFNN with particle swarm optimized weights and biases. Firstly, the performance is tested on two benchmark databases for neural network, The Breast Cancer Database and the Diabetic Database. Result shows that neural network performs better with initial weights and biases obtained by Particle Swarm optimization. The network converges faster with PSO obtained initial weights and biases for FFNN and classification accuracy is increased.
Texture features based text extraction from images using DWT and K-means clus...Divya Gera
Text extraction from different kind of images document, caption and scene text images. Discret wavelet transform was used to exract horizontal, vertical and diagonal features and k-means clustering was used to cluster the features into text and background cluster. For simple images k = 2 worked i.e. text and backgroud cluster while for complex images k=3 was used i.e. text cluster, complex background ad simple background.
A Parallel Framework For Multilayer Perceptron For Human Face RecognitionCSCJournals
Artificial neural networks have already shown their success in face recognition and similar complex pattern recognition tasks. However, a major disadvantage of the technique is that it is extremely slow during training for larger classes and hence not suitable for real-time complex problems such as pattern recognition. This is an attempt to develop a parallel framework for the training algorithm of a perceptron. In this paper, two general architectures for a Multilayer Perceptron (MLP) have been demonstrated. The first architecture is All-Class-in-One-Network (ACON) where all the classes are placed in a single network and the second one is One-Class-in-One-Network (OCON) where an individual single network is responsible for each and every class. Capabilities of these two architectures were compared and verified in solving human face recognition, which is a complex pattern recognition task where several factors affect the recognition performance like pose variations, facial expression changes, occlusions, and most importantly illumination changes. Experimental results show that the proposed OCON structure performs better than the conventional ACON in terms of network training convergence speed and which can be easily exercised in a parallel environment.
Sparse representation based classification of mr images of brain for alzheime...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A lightweight secure scheme for detecting provenance forgery and packet drop ...LeMeniz Infotech
A lightweight secure scheme for detecting provenance forgery and packet drop attacks in wireless sensor networks
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Visit : www.lemenizinfotech.com / www.ieeemaster.com
Mail : projects@lemenizinfotech.com
k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells.
BRAIN TUMOR MRI IMAGE SEGMENTATION AND DETECTION IN IMAGE PROCESSINGDharshika Shreeganesh
Image processing is an active research area in which medical image processing is a highly challenging field. Medical imaging
techniques are used to image the inner portions of the human body for medical diagnosis. Brain tumor is a serious life altering
disease condition. Image segmentation plays a significant role in image processing as it helps in the extraction of suspicious regions
from the medical images. In this paper we have proposed segmentation of brain MRI image using K-means clustering algorithm
followed by morphological filtering which avoids the misclustered regions that can inevitably be formed after segmentation of the brain MRI image for detection of tumor location.
Optical character recognition an encompassing revieweSAT Journals
Abstract
Optical character recognition (OCR) is becoming a powerful tool in the field of Character Recognition, now a days. In the existing globalized environment, OCR can play a vital role in different application fields. Basically, OCR technique converts images into editable format. This technique converts images in the form of documents such as we can edit, modify and store data more safely for longtime. This paper presents basic of OCR technique with its components such as pre-processing, Feature Extraction, Classification, post-processing etc. There are various techniques have been implemented for the recognition of character. This Review also discusses different ideas implemented earlier for recognition of a character. This paper may act as a supportive material for those who wish to know about OCR.
Keywords- OCR, Feature Extraction
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
With the surge in modern research focus towards Pervasive Computing, lot of techniques and challenges
needs to be addressed so as to effectively create smart spaces and achieve miniaturization. In the process of
scaling down to compact devices, the real things to ponder upon are the Information Retrieval challenges.
In this work, we discuss the aspects of multimedia which makes information access challenging. An
Example Pattern Recognition scenario is presented and the mathematical techniques that can be used to
model uncertainty are also presented for developing a system that can sense, compute and communicate in
a way that can make human life easy with smart objects assisting from around his surroundings.
Enhancing the performance of cluster based text summarization using support v...eSAT Journals
Abstract Technology is evolving day by day and this increase in technology is nothing but is the efforts to reduce human work and to have systems as automatic as possible. Same thing is true in terms of existence of digital information. Due to enormous increase in the use of internet, there is striking increase in the digital information. This digital information is characterized by different form of information, same information in different form, unrelated information and also there is lot of redundant information. Another next important thing to note is that most of the time we require textual information. To search or retrieve small information one has to go through thousands of documents, read all the retrieved documents irrespective whether they contain useful information or no. It becomes very difficult to read all the retrieved documents and prepare exact summary out of it within time. Besides this, many times retrieved information is repeated in almost many documents. This leads to research in the area of text mining. Text summarization is one of the challenging tasks in the field of text mining. Keywords: Entropy, FCM, Purity, SVM
Review paper on segmentation methods for multiobject feature extractioneSAT Journals
Abstract Feature extraction and representation plays a vital role in multimedia processing. It is still a challenge in computer vision system to extract ideal features that represents intrinsic characteristics of an image. Multiobject feature extraction system means a system that can extract features and locations of multiple objects in an image. In this paper we have discuss various methods to extract location and features of multiple objects and describe a system that can extract locations and features of multiple objects in an image by implementing an algorithm as hardware logic on a field-programmable gate array-based platform. There are many multiobject extraction methods which can be use for image segmentation based on motion, color intensity and texture. By calculating zeroth and first order moments of objects it is possible to obtain locations and sizes of multiple objects in an image. Keywords: multiobject extraction, image segmentation
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Abstract Learning Analytics by nature relies on computational information processing activities intended to extract from raw data some interesting aspects that can be used to obtain insights into the behaviors of learners, the design of learning experiences, etc. There is a large variety of computational techniques that can be employed, all with interesting properties, but it is the interpretation of their results that really forms the core of the analytics process. As a rising subject, data mining and business intelligence are playing an increasingly important role in the decision support activity of every walk of life. The Variance Rover System (VRS) mainly focused on the large data sets obtained from online web visiting and categorizing this into clusters according some similarity and the process of predicting customer behavior and selecting actions to influence that behavior to benefit the company, so as to take optimized and beneficial decisions of business expansion. Keywords: Analytics, Business intelligence, Clustering, Data Mining, Standard K-means, Optimized K-means
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Isolated word recognition using lpc & vector quantizationeSAT Journals
Abstract Speech recognition is always looked upon as a fascinating field in human computer interaction. It is one of the fundamental steps towards understanding human recognition and their behavior. This paper explicates the theory and implementation of Speech recognition. This is a speaker-dependent real time isolated word recognizer. The major logic used was to first obtain the feature vectors using LPC which was followed by vector quantization. The quantized vectors were then recognized by measuring the Minimum average distortion. All Speech Recognition systems contain Two Main Phases, namely Training Phase and Testing Phase. In the Training Phase, the Features of the words are extracted and during the recognition phase feature matching Takes place. The feature or the template thus extracted is stored in the data base, during the recognition phase the extracted features are compared with the template in the database. The features of the words are extracted by using LPC analysis. Vector Quantization is used for generating the code books. Finally the recognition decision is made based on the matching score. MATLAB will be used to implement this concept to achieve further understanding. Index Terms: Speech Recognition, LPC, Vector Quantization, and Code Book.
3 d mrf based video tracking in the compressed domaineSAT Journals
Abstract Object tracking is an interesting and needed procedure for many real time applications. But it is a challenging one, because of the presence of challenging sequences with abrupt motion, drastic illumination change, large pose variation, occlusion, cluttered background and also the camera shake. This paper presents a novel method of object tracking by using the algorithms spatio-temporal Markov random field (STMRF) and online discriminative feature selection (ODFS), which overcome the above mentioned problems and provide a better tracking process. This method is also capable of tracking multiple objects in video sequence even in the presence of an object interactions and occlusions that achieves better results with real time performance. Keywords: Video object tracking, spatio-temporal Markov random field (ST-MRF), online discriminative feature selection (ODFS).
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Object extraction using edge, motion and saliency information from videoseSAT Journals
Abstract Object detection is a process of finding the instances of object of a certain class which is useful in analysis of video or image. There are number of algorithms have been developed so far for object detection. Object detection has got significant role in variety of areas of computer vision like video surveillance, image retrieval`. In this paper presented an efficient algorithm for moving object extraction using edge, motion and saliency information from videos. Out methodology includes 4 stages: Frame generation, Pre-processing, Foreground generation and integration of cues. Foreground generation includes edge detection using sobel edge detection algorithm, motion detection using pixel-based absolute difference algorithm and motion saliency detection. Conditional Random Field (CRF) is applied for integration of cues and thus we get better spatial information of segmented object. Keywords: Object detection, Saliency information, Sobel edge detection, CRF.
Performance comparison of blind adaptive multiuser detection algorithmseSAT Journals
Abstract Blind multiuser detection algorithms are used to eliminate the Multiple Access Interference (MAI) and the Near-Far effect in mobile communication systems. Four kinds of blind multiuser detection algorithms applied to code-division multiple-access (CDMA) communication system are studied in this paper. Those algorithms are the Least Mean Squares (LMS), Recursive Least Squares (RLS), Kalman filter and subspace-based Kalman filter algorithms. The resultant signal to interference ratio (SIR) at the output of the receivers controlled by the four kinds of multi-user detection algorithm has been discussed in this paper. Simulation results show that the subspace based Kalman filter algorithm outperforms all other three algorithms. Subspace-based Kalman filter algorithm has faster convergence speed, more practical and the capability of CDMA system can be increased. Keywords: Blind multiuser detection, Code-division multiple access, Mean output energy, Adaptive filtering.
MAGNETIC RESONANCE BRAIN IMAGE SEGMENTATIONVLSICS Design
Segmentation of tissues and structures from medical images is the first step in many image analysis applications developed for medical diagnosis. With the growing research on medical image segmentation, it is essential to categorize the research outcomes and provide researchers with an overview of the existing segmentation techniques in medical images. In this paper, different image segmentation methods applied on magnetic resonance brain images are reviewed. The selection of methods includes sources from image processing journals, conferences, books, dissertations and thesis. The conceptual details of the methods are explained and mathematical details are avoided for simplicity. Both broad and detailed categorizations of reviewed segmentation techniques are provided. The state of art research is provided with emphasis on developed techniques and image properties used by them. The methods defined are not always mutually independent. Hence, their inter relationships are also stated. Finally, conclusions are drawn summarizing commonly used techniques and their complexities in application.
Similar to Dynamic thresholding on speech segmentation (20)
Mechanical properties of hybrid fiber reinforced concrete for pavementseSAT Journals
Abstract
The effect of addition of mono fibers and hybrid fibers on the mechanical properties of concrete mixture is studied in the present
investigation. Steel fibers of 1% and polypropylene fibers 0.036% were added individually to the concrete mixture as mono fibers and
then they were added together to form a hybrid fiber reinforced concrete. Mechanical properties such as compressive, split tensile and
flexural strength were determined. The results show that hybrid fibers improve the compressive strength marginally as compared to
mono fibers. Whereas, hybridization improves split tensile strength and flexural strength noticeably.
Keywords:-Hybridization, mono fibers, steel fiber, polypropylene fiber, Improvement in mechanical properties.
Material management in construction – a case studyeSAT Journals
Abstract
The objective of the present study is to understand about all the problems occurring in the company because of improper application
of material management. In construction project operation, often there is a project cost variance in terms of the material, equipments,
manpower, subcontractor, overhead cost, and general condition. Material is the main component in construction projects. Therefore,
if the material management is not properly managed it will create a project cost variance. Project cost can be controlled by taking
corrective actions towards the cost variance. Therefore a methodology is used to diagnose and evaluate the procurement process
involved in material management and launch a continuous improvement was developed and applied. A thorough study was carried
out along with study of cases, surveys and interviews to professionals involved in this area. As a result, a methodology for diagnosis
and improvement was proposed and tested in selected projects. The results obtained show that the main problem of procurement is
related to schedule delays and lack of specified quality for the project. To prevent this situation it is often necessary to dedicate
important resources like money, personnel, time, etc. To monitor and control the process. A great potential for improvement was
detected if state of the art technologies such as, electronic mail, electronic data interchange (EDI), and analysis were applied to the
procurement process. These helped to eliminate the root causes for many types of problems that were detected.
Managing drought short term strategies in semi arid regions a case studyeSAT Journals
Abstract
Drought management needs multidisciplinary action. Interdisciplinary efforts among the experts in various fields of the droughts
prone areas are helpful to achieve tangible and permanent solution for this recurring problem. The Gulbarga district having the total
area around 16, 240 sq.km, and accounts 8.45 per cent of the Karnataka state area. The district has been situated with latitude 17º 19'
60" North and longitude of 76 º 49' 60" east. The district is situated entirely on the Deccan plateau positioned at a height of 300 to
750 m above MSL. Sub-tropical, semi-arid type is one among the drought prone districts of Karnataka State. The drought
management is very important for a district like Gulbarga. In this paper various short term strategies are discussed to mitigate the
drought condition in the district.
Keywords: Drought, South-West monsoon, Semi-Arid, Rainfall, Strategies etc.
Life cycle cost analysis of overlay for an urban road in bangaloreeSAT Journals
Abstract
Pavements are subjected to severe condition of stresses and weathering effects from the day they are constructed and opened to traffic
mainly due to its fatigue behavior and environmental effects. Therefore, pavement rehabilitation is one of the most important
components of entire road systems. This paper highlights the design of concrete pavement with added mono fibers like polypropylene,
steel and hybrid fibres for a widened portion of existing concrete pavement and various overlay alternatives for an existing
bituminous pavement in an urban road in Bangalore. Along with this, Life cycle cost analyses at these sections are done by Net
Present Value (NPV) method to identify the most feasible option. The results show that though the initial cost of construction of
concrete overlay is high, over a period of time it prove to be better than the bituminous overlay considering the whole life cycle cost.
The economic analysis also indicates that, out of the three fibre options, hybrid reinforced concrete would be economical without
compromising the performance of the pavement.
Keywords: - Fatigue, Life cycle cost analysis, Net Present Value method, Overlay, Rehabilitation
Laboratory studies of dense bituminous mixes ii with reclaimed asphalt materialseSAT Journals
Abstract
The issue of growing demand on our nation’s roadways over that past couple of decades, decreasing budgetary funds, and the need to
provide a safe, efficient, and cost effective roadway system has led to a dramatic increase in the need to rehabilitate our existing
pavements and the issue of building sustainable road infrastructure in India. With these emergency of the mentioned needs and this
are today’s burning issue and has become the purpose of the study.
In the present study, the samples of existing bituminous layer materials were collected from NH-48(Devahalli to Hassan) site.The
mixtures were designed by Marshall Method as per Asphalt institute (MS-II) at 20% and 30% Reclaimed Asphalt Pavement (RAP).
RAP material was blended with virgin aggregate such that all specimens tested for the, Dense Bituminous Macadam-II (DBM-II)
gradation as per Ministry of Roads, Transport, and Highways (MoRT&H) and cost analysis were carried out to know the economics.
Laboratory results and analysis showed the use of recycled materials showed significant variability in Marshall Stability, and the
variability increased with the increase in RAP content. The saving can be realized from utilization of recycled materials as per the
methodology, the reduction in the total cost is 19%, 30%, comparing with the virgin mixes.
Keywords: Reclaimed Asphalt Pavement, Marshall Stability, MS-II, Dense Bituminous Macadam-II
Laboratory investigation of expansive soil stabilized with natural inorganic ...eSAT Journals
Abstract
Soil stabilization has proven to be one of the oldest techniques to improve the soil properties. Literature review conducted revealed
that uses of natural inorganic stabilizers are found to be one of the best options for soil stabilization. In this regard an attempt has
been made to evaluate the influence of RBI-81 stabilizer on properties of black cotton soil through laboratory investigations. Black
cotton soil with varying percentages of RBI-81 viz., 0, 0.5, 1, 1.5, 2, and 2.5 percent were studied for moisture density relationships
and strength behaviour of soils. Also the effect of curing period was evaluated as literature review clearly emphasized the strength
gain of soils stabilized with RBI-81 over a period of time. The results obtained shows that the unconfined compressive strength of
specimens treated with RBI-81 increased approximately by 250% for a curing period of 28 days as compared to virgin soil. Further
the CBR value improved approximately by 400%. The studies indicated an increasing trend for soil strength behaviour with
increasing percentage of RBI-81 suggesting its potential applications in soil stabilization.
Influence of reinforcement on the behavior of hollow concrete block masonry p...eSAT Journals
Abstract
Reinforced masonry was developed to exploit the strength potential of masonry and to solve its lack of tensile strength. Experimental
and analytical studies have been carried out to investigate the effect of reinforcement on the behavior of hollow concrete block
masonry prisms under compression and to predict ultimate failure compressive strength. In the numerical program, three dimensional
non-linear finite elements (FE) model based on the micro-modeling approach is developed for both unreinforced and reinforced
masonry prisms using ANSYS (14.5). The proposed FE model uses multi-linear stress-strain relationships to model the non-linear
behavior of hollow concrete block, mortar, and grout. Willam-Warnke’s five parameter failure theory has been adopted to model the
failure of masonry materials. The comparison of the numerical and experimental results indicates that the FE models can successfully
capture the highly nonlinear behavior of the physical specimens and accurately predict their strength and failure mechanisms.
Keywords: Structural masonry, Hollow concrete block prism, grout, Compression failure, Finite element method,
Numerical modeling.
Influence of compaction energy on soil stabilized with chemical stabilizereSAT Journals
Abstract
Increase in traffic along with heavier magnitude of wheel loads cause rapid deterioration in pavements. There is a need to improve
density, strength of soil subgrade and other pavement layers. In this study an attempt is made to improve the properties of locally
available loamy soil using twin approaches viz., i) increasing the compaction of soil and ii) treating the soil with chemical stabilizer.
Laboratory studies are carried out on both untreated and treated soil samples compacted by different compaction efforts. Studies
show that increase in compaction effort results in increase in density of soil. However in soil treated with chemical stabilizer, rate of
increase in density is not significant. The soil treated with chemical stabilizer exhibits improvement in both strength and performance
properties.
Keywords: compaction, density, subgradestabilization, resilient modulus
Geographical information system (gis) for water resources managementeSAT Journals
Abstract
Water resources projects are inherited with overlapping and at times conflicting objectives. These projects are often of varied sizes
ranging from major projects with command areas of millions of hectares to very small projects implemented at the local level. Thus,
in all these projects there is seldom proper coordination which is essential for ensuring collective sustainability.
Integrated watershed development and management is the accepted answer but in turn requires a comprehensive framework that can
enable planning process involving all the stakeholders at different levels and scales is compulsory. Such a unified hydrological
framework is essential to evaluate the cause and effect of all the proposed actions within the drainage basins.
The present paper describes a hydrological framework developed in the form of a Hydrologic Information System (HIS) which is
intended to meet the specific information needs of the various line departments of a typical State connected with water related aspects.
The HIS consist of a hydrologic information database coupled with tools for collating primary and secondary data and tools for
analyzing and visualizing the data and information. The HIS also incorporates hydrological model base for indirect assessment of
various entities of water balance in space and time. The framework would be maintained and updated to reflect fully the most
accurate ground truth data and the infrastructure requirements for planning and management.
Keywords: Hydrological Information System (HIS); WebGIS; Data Model; Web Mapping Services
Forest type mapping of bidar forest division, karnataka using geoinformatics ...eSAT Journals
Abstract
The study demonstrate the potentiality of satellite remote sensing technique for the generation of baseline information on forest types
including tree plantation details in Bidar forest division, Karnataka covering an area of 5814.60Sq.Kms. The Total Area of Bidar
forest division is 5814Sq.Kms analysis of the satellite data in the study area reveals that about 84% of the total area is Covered by
crop land, 1.778% of the area is covered by dry deciduous forest, 1.38 % of mixed plantation, which is very threatening to the
environmental stability of the forest, future plantation site has been mapped. With the use of latest Geo-informatics technology proper
and exact condition of the trees can be observed and necessary precautions can be taken for future plantation works in an appropriate
manner
Keywords:-RS, GIS, GPS, Forest Type, Tree Plantation
Factors influencing compressive strength of geopolymer concreteeSAT Journals
Abstract
To study effects of several factors on the properties of fly ash based geopolymer concrete on the compressive strength and also the
cost comparison with the normal concrete. The test variables were molarities of sodium hydroxide(NaOH) 8M,14M and 16M, ratio of
NaOH to sodium silicate (Na2SiO3) 1, 1.5, 2 and 2.5, alkaline liquid to fly ash ratio 0.35 and 0.40 and replacement of water in
Na2SiO3 solution by 10%, 20% and 30% were used in the present study. The test results indicated that the highest compressive
strength 54 MPa was observed for 16M of NaOH, ratio of NaOH to Na2SiO3 2.5 and alkaline liquid to fly ash ratio of 0.35. Lowest
compressive strength of 27 MPa was observed for 8M of NaOH, ratio of NaOH to Na2SiO3 is 1 and alkaline liquid to fly ash ratio of
0.40. Alkaline liquid to fly ash ratio of 0.35, water replacement of 10% and 30% for 8 and 16 molarity of NaOH and has resulted in
compressive strength of 36 MPa and 20 MPa respectively. Superplasticiser dosage of 2 % by weight of fly ash has given higher
strength in all cases.
Keywords: compressive strength, alkaline liquid, fly ash
Experimental investigation on circular hollow steel columns in filled with li...eSAT Journals
Abstract
Composite Circular hollow Steel tubes with and without GFRP infill for three different grades of Light weight concrete are tested for
ultimate load capacity and axial shortening , under Cyclic loading. Steel tubes are compared for different lengths, cross sections and
thickness. Specimens were tested separately after adopting Taguchi’s L9 (Latin Squares) Orthogonal array in order to save the initial
experimental cost on number of specimens and experimental duration. Analysis was carried out using ANN (Artificial Neural
Network) technique with the assistance of Mini Tab- a statistical soft tool. Comparison for predicted, experimental & ANN output is
obtained from linear regression plots. From this research study, it can be concluded that *Cross sectional area of steel tube has most
significant effect on ultimate load carrying capacity, *as length of steel tube increased- load carrying capacity decreased & *ANN
modeling predicted acceptable results. Thus ANN tool can be utilized for predicting ultimate load carrying capacity for composite
columns.
Keywords: Light weight concrete, GFRP, Artificial Neural Network, Linear Regression, Back propagation, orthogonal
Array, Latin Squares
Experimental behavior of circular hsscfrc filled steel tubular columns under ...eSAT Journals
Abstract
This paper presents an outlook on experimental behavior and a comparison with predicted formula on the behaviour of circular
concentrically loaded self-consolidating fibre reinforced concrete filled steel tube columns (HSSCFRC). Forty-five specimens were
tested. The main parameters varied in the tests are: (1) percentage of fiber (2) tube diameter or width to wall thickness ratio (D/t
from 15 to 25) (3) L/d ratio from 2.97 to 7.04 the results from these predictions were compared with the experimental data. The
experimental results) were also validated in this study.
Keywords: Self-compacting concrete; Concrete-filled steel tube; axial load behavior; Ultimate capacity.
Evaluation of punching shear in flat slabseSAT Journals
Abstract
Flat-slab construction has been widely used in construction today because of many advantages that it offers. The basic philosophy in
the design of flat slab is to consider only gravity forces; this method ignores the effect of punching shear due to unbalanced moments
at the slab column junction which is critical. An attempt has been made to generate generalized design sheets which accounts both
punching shear due to gravity loads and unbalanced moments for cases (a) interior column; (b) edge column (bending perpendicular
to shorter edge); (c) edge column (bending parallel to shorter edge); (d) corner column. These design sheets are prepared as per
codal provisions of IS 456-2000. These design sheets will be helpful in calculating the shear reinforcement to be provided at the
critical section which is ignored in many design offices. Apart from its usefulness in evaluating punching shear and the necessary
shear reinforcement, the design sheets developed will enable the designer to fix the depth of flat slab during the initial phase of the
design.
Keywords: Flat slabs, punching shear, unbalanced moment.
Evaluation of performance of intake tower dam for recent earthquake in indiaeSAT Journals
Abstract
Intake towers are typically tall, hollow, reinforced concrete structures and form entrance to reservoir outlet works. A parametric
study on dynamic behavior of circular cylindrical towers can be carried out to study the effect of depth of submergence, wall thickness
and slenderness ratio, and also effect on tower considering dynamic analysis for time history function of different soil condition and
by Goyal and Chopra accounting interaction effects of added hydrodynamic mass of surrounding and inside water in intake tower of
dam
Key words: Hydrodynamic mass, Depth of submergence, Reservoir, Time history analysis,
Evaluation of operational efficiency of urban road network using travel time ...eSAT Journals
Abstract
Efficiency of the road network system is analyzed by travel time reliability measures. The study overlooks on an important measure of
travel time reliability and prioritizing Tiruchirappalli road network. Traffic volume and travel time were collected using license plate
matching method. Travel time measures were estimated from average travel time and 95th travel time. Effect of non-motorized vehicle
on efficiency of road system was evaluated. Relation between buffer time index and traffic volume was created. Travel time model has
been developed and travel time measure was validated. Then service quality of road sections in network were graded based on
travel time reliability measures.
Keywords: Buffer Time Index (BTI); Average Travel Time (ATT); Travel Time Reliability (TTR); Buffer Time (BT).
Estimation of surface runoff in nallur amanikere watershed using scs cn methodeSAT Journals
Abstract
The development of watershed aims at productive utilization of all the available natural resources in the entire area extending from
ridge line to stream outlet. The per capita availability of land for cultivation has been decreasing over the years. Therefore, water and
the related land resources must be developed, utilized and managed in an integrated and comprehensive manner. Remote sensing and
GIS techniques are being increasingly used for planning, management and development of natural resources. The study area, Nallur
Amanikere watershed geographically lies between 110 38’ and 110 52’ N latitude and 760 30’ and 760 50’ E longitude with an area of
415.68 Sq. km. The thematic layers such as land use/land cover and soil maps were derived from remotely sensed data and overlayed
through ArcGIS software to assign the curve number on polygon wise. The daily rainfall data of six rain gauge stations in and around
the watershed (2001-2011) was used to estimate the daily runoff from the watershed using Soil Conservation Service - Curve Number
(SCS-CN) method. The runoff estimated from the SCS-CN model was then used to know the variation of runoff potential with different
land use/land cover and with different soil conditions.
Keywords: Watershed, Nallur watershed, Surface runoff, Rainfall-Runoff, SCS-CN, Remote Sensing, GIS.
Estimation of morphometric parameters and runoff using rs & gis techniqueseSAT Journals
Abstract
Land and water are the two vital natural resources, the optimal management of these resources with minimum adverse environmental
impact are essential not only for sustainable development but also for human survival. Satellite remote sensing with geographic
information system has a pragmatic approach to map and generate spatial input layers of predicting response behavior and yield of
watershed. Hence, in the present study an attempt has been made to understand the hydrological process of the catchment at the
watershed level by drawing the inferences from moprhometric analysis and runoff. The study area chosen for the present study is
Yagachi catchment situated in Chickamaglur and Hassan district lies geographically at a longitude 75⁰52’08.77”E and
13⁰10’50.77”N latitude. It covers an area of 559.493 Sq.km. Morphometric analysis is carried out to estimate morphometric
parameters at Micro-watershed to understand the hydrological response of the catchment at the Micro-watershed level. Daily runoff
is estimated using USDA SCS curve number model for a period of 10 years from 2001 to 2010. The rainfall runoff relationship of the
study shows there is a positive correlation.
Keywords: morphometric analysis, runoff, remote sensing and GIS, SCS - method
-
Effect of variation of plastic hinge length on the results of non linear anal...eSAT Journals
Abstract The nonlinear Static procedure also well known as pushover analysis is method where in monotonically increasing loads are applied to the structure till the structure is unable to resist any further load. It is a popular tool for seismic performance evaluation of existing and new structures. In literature lot of research has been carried out on conventional pushover analysis and after knowing deficiency efforts have been made to improve it. But actual test results to verify the analytically obtained pushover results are rarely available. It has been found that some amount of variation is always expected to exist in seismic demand prediction of pushover analysis. Initial study is carried out by considering user defined hinge properties and default hinge length. Attempt is being made to assess the variation of pushover analysis results by considering user defined hinge properties and various hinge length formulations available in literature and results compared with experimentally obtained results based on test carried out on a G+2 storied RCC framed structure. For the present study two geometric models viz bare frame and rigid frame model is considered and it is found that the results of pushover analysis are very sensitive to geometric model and hinge length adopted. Keywords: Pushover analysis, Base shear, Displacement, hinge length, moment curvature analysis
Effect of use of recycled materials on indirect tensile strength of asphalt c...eSAT Journals
Abstract
Depletion of natural resources and aggregate quarries for the road construction is a serious problem to procure materials. Hence
recycling or reuse of material is beneficial. On emphasizing development in sustainable construction in the present era, recycling of
asphalt pavements is one of the effective and proven rehabilitation processes. For the laboratory investigations reclaimed asphalt
pavement (RAP) from NH-4 and crumb rubber modified binder (CRMB-55) was used. Foundry waste was used as a replacement to
conventional filler. Laboratory tests were conducted on asphalt concrete mixes with 30, 40, 50, and 60 percent replacement with RAP.
These test results were compared with conventional mixes and asphalt concrete mixes with complete binder extracted RAP
aggregates. Mix design was carried out by Marshall Method. The Marshall Tests indicated highest stability values for asphalt
concrete (AC) mixes with 60% RAP. The optimum binder content (OBC) decreased with increased in RAP in AC mixes. The Indirect
Tensile Strength (ITS) for AC mixes with RAP also was found to be higher when compared to conventional AC mixes at 300C.
Keywords: Reclaimed asphalt pavement, Foundry waste, Recycling, Marshall Stability, Indirect tensile strength.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 09 | Sep-2013, Available @ http://www.ijret.org 404
DYNAMIC THRESHOLDING ON SPEECH SEGMENTATION
Md. Mijanur Rahman1
, Md. Al-Amin Bhuiyan2
1
Assistant Professor, Dept. of Computer Science & Engineering, Jatiya Kabi Kazi Nazrul Islam University, Bangladesh
2
Professor, Dept. of Computer Science & Engineering, Jahangirnagar University, Bangladesh
mijan_cse@yahoo.com, alamin_bhuiyan@yahoo.com
Abstract
Word is the preferred and natural unit of speech, because word units have well defined acoustic representation. This paper presents
several dynamic thresholding approaches for segmenting continuous Bangla speech sentences into words/sub-words. We have
proposed three efficient methods for speech segmentation: two of them are usually used in pattern classification (i.e., k-means and
FCM clustering) and one of them is used in image segmentation (i.e., Otsu’s thresholding method). We also used new approaches
blocking black area and boundary detection techniques to properly detect word boundaries in continuous speech and label the entire
speech sentence into a sequence of words/sub-words. K-Means and FCM clustering methods produce better segmentation results than
that of Otsu’s Method. All the algorithms and methods used in this research are implemented in MATLAB and the proposed system
achieved the average segmentation accuracy of 94% approximately.
Keywords: Blocking Black Area, Clustering, Dynamic Thresholding, Fuzzy Logic and Speech Segmentation.
----------------------------------------------------------------------***----------------------------------------------------------------------
1. INTRODUCTION
Automated segmentation of speech has been a subject of study
for over 30 years [1] and it plays a central role in many speech
processing and ASR applications. It is important to various
automated speech processing algorithms: speech recognition,
speech corpus collection, speaker verification, etc., in the
research field of natural language processing [2,3]. The
traditional or manual segmentation approach is impractical for
very large data bases. It is extremely laborious and tedious.
This is why automated methods are widely utilized. Common
approach to speech signal zone identification is using a
threshold value. In many papers speech segmentation is done
by using wavelet [4], fuzzy methods [5], artificial neural
networks [6] and hidden Markov models [7]. This paper
proposed several pattern classification and image
segmentation methods for segmenting continuous Bangla
speech into words/sub-words. To do so, we have used the
modified version of k-means, fuzzy c-means and Otsu‟s
algorithms with blocking black area method and shape
identification.
The paper is organized as follows: Section 1 describes the
introduction of speech processing and the organization of this
paper. In Section 2, we will discuss about speech segmentation
and types of segmentation. Section 3 will describe pattern
clustering and different clustering algorithms. In Section 4,
Otsu‟s thresholding method will be discussed. The
methodological steps of the proposed system will be described
in Section 5. Sections 6 and 7 will describe the experimental
results and conclusion, respectively.
2. SPEECH SEGMENTATION
Speech recognition system requires segmentation of speech
signal into discrete, non-overlapping acoustic units [8][9]. It
can be the segment, phone, syllable, word, sentence or dialog
turn level. Word is the preferred and natural units of speech
because word units have well defined acoustic representation.
So, we have been chosen word as our basic unit. Automatic
speech segmentation methods can be classified in many ways,
but one very common classification is the division to blind and
aided segmentation algorithms [10]. A central difference
between aided and blind methods is in how much the
segmentation algorithm uses previously obtained data or
external knowledge to process the expected speech. The term
blind segmentation refers to methods where there is no pre-
existing or external knowledge regarding linguistic properties,
such as orthography or the full phonetic annotation, of the
signal to be segmented. On the other hand, Aided
segmentation algorithms use some sort of external linguistic
knowledge of the speech stream to segment it into
corresponding segments of the desired type. Due to the lack of
external information, the first phase of blind segmentation
relies entirely on the acoustical features present in the signal.
The second phase is usually built on a front-end processing of
the speech signal using MFCC, LP-coefficients, or pure FFT
spectrum [11]. In our research works, we have used FFT
spectrum (such as, spectrogram) features of speech signal.
3. CLUSTERING
Clustering is the process of assigning a set of objects into a set
of disjoint groups called clusters so that objects in each same
cluster are more similar to each other than objects from
2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 09 | Sep-2013, Available @ http://www.ijret.org 405
different clusters. Clustering techniques are applied in many
application areas such as pattern recognition [12], data mining
[13], machine learning [14], etc. Clustering algorithms can be
broadly classified as Hard, Fuzzy, Possibilistic, and
Probabilistic [15], each of which has its own special
characteristics. There are a lot of applications of clustering
methods, range from unsupervised learning of neural network,
Pattern recognitions, Classification analysis, Artificial
intelligent, image processing, machine vision, etc. Several
clustering methods have been widely studied and successfully
applied in image segmentation [16–22].
In this paper, the hard and fuzzy clustering schemes have been
introduced to get the optimal threshold in speech
segmentation. The conventional hard clustering method
restricts each point of the data set to exclusively just one
cluster. So the membership values to be either 0 or 1. The K-
Means clustering algorithm is widely used as hard clustering
method. On the other hand, the fuzzy clustering method allows
an object to belong to several clusters at the same time, but
with the different degrees of membership between 0 and 1.
The fuzzy C-means algorithm is the most popular fuzzy
clustering method used in pattern classification.
3.1 K-Means Clustering Algorithm
K-Means Clustering is one of the unsupervised learning
algorithms, first used by James MacQueen in 1967 [23] and
first proposed by Stuart Lloyd in 1957 as a technique for
pulse-code modulation [24]. It is also referred to as Lloyd's
algorithm [25]. Here, the modified algorithm is used to
compute the threshold from speech spectrogram. The
algorithm classifies a given data set into a certain number
of clusters (i.e., k clusters) based on distance measures and to
define k-centers, one for each cluster and finally computes the
threshold. This algorithm is an iterative process until no new
moves of data, as shown in Figure-1. Finally,
this algorithm aims at minimizing an objective function, also
known as squared error function and given by:
k
i
c
j
j
j
i
i
vxJ
1 1
2)(
Where:
j
j
i vx )(
is the Euclidean distance between a data point (xi)
and the cluster center, (vj);
‘ci’ is the number of data points in ith
cluster; and
‘k’ is the number of cluster centers.
The algorithmic steps for calculating a threshold using k-
means clustering is given below:
Let x = {x1, x2, x3,…,xn} be the set of data values in speech
spectrogram.
1) Assign the number of clusters, k=3 and define the 3 cluster
centers.
Let v = {v1,v2,v3} be the set of 3 cluster centers.
2) Calculate the distance (dij) between ith
data and jth
cluster
center.
3) Assign each data to the closest cluster with minimum
distance.
4) Recalculate the new cluster center using:
ic
j
j
i
i x
c
v
1
1
where, ‘ci’ represents the number of data points in ith
cluster.
5) Recalculate the distance between each data and new
obtained cluster centers.
6) If no data was reassigned then stop, otherwise repeat from
step (3).
7) Calculate the desired threshold from the average of 3
cluster centers.
Figure1. K-Means Clustering Algorithm - Calculating the
desired threshold.
3.2 FCM Clustering Algorithm
The algorithm is developed by J C Bezdek in 1973 for pattern
classification [26], and first reported by J C Dunn in 1974
[27], later J C Bezdek used this algorithm for pattern
recognition [28]. FCM is a generalization of K-Means. While
K-Means assigns each object to one and only one cluster,
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FCM allows clusters to be fuzzy sets, so that each object
belongs to all clusters with varying degrees of membership
and the following restriction: The sum of all membership
degrees for any given data point is equal to 1. It works by
assigning membership to each object on the basis of distance
between the cluster center and the object. More the object is
near to the cluster center more is its membership. The
algorithm is an iteration process, as shown in Figure-2. After
each iteration, membership and cluster centers are updated,
and finally compute a threshold from the cluster centroids.
The algorithmic step for calculating a threshold using fuzzy c-
means clustering is given below:
Let x = {x1, x2, x3, ..., xn} be the set of data values in speech
spectrogram.
1) Assign the number of cluster, c=3 and define the cluster
centers.
Let v = {v1, v2, v3, v3} be the set of 3 cluster centers.
2) Calculate the Euclidean distance (dij) between ith
data and
jth
cluster center.
3) Update the fuzzy membership function (µij) using:
cjnidd
c
k
m
ikijij ,...,2,1;,...,2,1,/1
1
)1/(2
4) Compute the fuzzy centers 'vj' using:
cjxv
n
i
m
ij
n
i
i
m
ijj ,...,3,2,1,
11
wh
ere, m is the fuzziness index [1,∞].
5) Repeat from step (2) until the minimum 'J' value is
achieved or eUU kk
)()1(
.
where:
k is the iteration step;
e is the termination criterion between [0, 1];
cnijU *
is the fuzzy membership matrix; and
J is the objective function, obtained by:
c
j
n
i
ij
m
ij dJ
1 1
)(
6) Calculate the desired threshold from the average of 3
cluster centroids.
Figure2. FCM Clustering Algorithm - Calculating the desired
threshold.
4. OTSU’S THRESHOLDING METHOD
Thresholding is the simplest method of image segmentation;
can be used to create binary image from gray scale image. In
order to convert the image into a binary representation, first
we converted the image into a gray scale representation and
then performed particular threshold analysis [29]. Otsu‟s
method is a simple and effective automatic thresholding
method, invented by Nobuyuki Otsu in 1979 [30], also known
as binarization algorithm. It is used to automatically perform
histogram shape-based image thresholding; i.e. the reduction
of a grayscale image into a binary image. The algorithm
assumes that the image is composed of two basic classes:
Foreground and Background [30]. It then computes an optimal
threshold value that minimizes the weighted within class
variance; also maximizes the between class variance of these
two classes. Otsu‟s threshold is used in many applications
from medical imaging to low level computer vision. Our main
aim is to use Otsu‟s threshold in speech segmentation. Figure-
3 shows the step-wise Otsu‟s algorithm.
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4.1 Mathematical Formulation
The mathematical formulation of Otsu‟s method for
computing the optimum threshold is given below:
Let P(i) represents the image histogram of speech
spectrogram. The two class probabilities w1(t) and w2(t) at
level t are computed by:
t
i
iPtw
1
1 )()( And
I
ti
iPtw
1
2 )()(
The class means, μ1 (t) and μ2(t) are:
t
i tw
iiP
t
1 1
1
)(
)(
)( and
I
ti tw
iiP
t
1 2
2
)(
)(
)(
Individual class variances:
t
i tw
iP
tit
1 1
2
1
2
1
)(
)(
)]([)( And
I
ti tw
iP
tit
1 2
2
2
2
2
)(
)(
)]([)(
The within class variance (σw) is defined as a weighted sum
of variances of the two classes and given by:
)()()()()( 2
22
2
11
2
ttwttwtw
The between class variance (σb) is defined as a difference of
total variance and within class variance and given by:
)()()( 222
ttt wb 2
211 )]()()[()( tttwtw
These two variances σw and σb are calculated for all possible
thresholds, t = 0… I (max. intensity). Otsu finds the best
threshold that minimizes the weighted within class variance
(σw), also maximizes the weighted between class variance
(σb). Finally, the pixel luminance less than or equal to
threshold is replaced by 0 (black) and greater than threshold is
replaced by 1 (white) to obtain the binary or B/W image.
Figure3. Otsu‟s Thresholding Algorithm – Converting binary
image.
5. THE PROPOSED APPROACH
We proposed several clustering methods (k-means and fuzzy c-
means algorithms) and Otsu’s thresholding methods, with
blocking black area and boundary detection techniques, in
continuous Bangla speech segmentation. The proposed
segmentation system is shown in Figure-4 and will discuss in
the following sub-sections.
Figure4. Proposed Speech Segmentation System
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5.1 Speech Spectrogram
A spectrogram is a time-varying spectral representation of
signal. It shows how the spectral density of an audio signal
varies over time [31]. Spectrograms can be used to identify
spoken words phonetically. They are used extensively in the
development of the fields of music, sonar (sound navigation
and ranging), radar, and speech processing [32], etc.
The spectrogram is calculated by using the short-time Fourirer
Transform (STFT) of audio signal. The STFT of a signal
frame x[n] can be expressed by:
n
nj
emnnxmXmnxSTFT
][][,,][
Where: ][nx = signal; ][n = window function; m is
discrete and is continuous.
Thus, the spectrogram of the signal x[n] can be estimated by
computing the squares magnitude of the STFT of the signal
[33], i.e.,
2
,, nSTFTnmSpectrogra .
We used MATLAB‟s „spectrogram‟ function that converts
speech signal into spectrogram image. The spectrogram of the
speech sentence („আমাদের জাতীয় কবি কাজী নজরুল ইসলাম‟) is
shown in Figure-5.
(a) Original Speech Signal
(b) Spectrogram Image
Figure5. Spectrogram of speech signal „আমাদের জাতীয় কবি
কাজী নজরুল ইসলাম‟.
5.2 Dynamic Thresholding
First, we used MATLAB‟s „rgb2gray‟ function to convert
spectrogram RGB image to gray scale image with pixel values
ranging from 0 to 255; where 0 represents a fully black pixel
and 255 represents white pixel. Then we used „im2bw‟
function with a threshold to convert gray scale image to binary
image. But the problem for us is how we choose our threshold.
In our research, we proposed three efficient approaches, such
as, K-Means, FCM and Otsu‟s thresholding algorithm to
compute the desired threshold, valued between 0-1.
We used MATLAB‟s 3-class „kmeans‟ function and 3-class
„fcm‟ function. Both functions return the centroids of three
clusters. The average of 1st
and 2nd
largest centroids is
calculated as the desired threshold value. We also used
MATLAB‟s „graythresh‟ function that uses Otsu's
thresholding method, returns a level or threshold value for
which the intra-class variance of the black and white pixels is
minimum. The output image replaces all pixels in the input
image with luminance greater than or equal to the threshold
with the value of 1 (fully white) and less than threshold with 0
(fully black). Figure-6 shows the thresholded spectrogram
image of the speech sentence („আমাদের জাতীয় কবি কাজী
নজরুল ইসলাম‟).
5.3 Blocking Black Area Method
Here, we used a new approach „Blocking Black Area‟ method
in the thresholded spectrogram image that produces
rectangular black boxes in the voiced regions of the speech
sentence, as shown in Figure-7. The method works as follows:
Summing the column-wise intensity values of thresholded
spectrogram image.
Find the image columns with fewer white pixels based on
summing value and replace all pixels on this column with
luminance 0 (black).
Find the image columns with fewer black pixels based on
summing value and replace all pixels on this column with
luminance 1 (white).
(a) K-Means thresholded Image
(b) FCM thresholded Image
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(c) Otsu‟s thresholded Image
Figure6. Thresholded Spectrogram Images of Speech signal
„আমাদের জাতীয় কবি কাজী নজরুল ইসলাম‟
(a) Thresholded Spectrogram Image from Speech Signal
(b) After applying Blocking Black Area Method
Figure7. Effect of applying Blocking Black Area Method –
Producing rectangle black boxes in voiced regions of speech
signal
5.4 Boundary Detection
We used MATLAB „regionprops‟ function to measure the
properties of each connected object in the binary image. We
also used different shape measurements (such as 'Area',
'BoundingBox', 'Centroid') to identify each rectangular object
that represents speech words/sub-words. The 'Extrema'
measurement, which is a vector of [top-left top-right right-top
right-bottom bottom-right bottom-left left-bottom left-top], is
used to detect the start (bottom-left) and end (bottom-right)
points of each rectangular object, as shown in Figure-8.
Figure8. Star and End point Detection of rectangular object.
5.5 Final Speech Segments
Each rectangular black box represents a speech word. After
detecting the start and end points of each black box, the word
boundaries of the original speech sentence are marked
automatically by these two points and finally we have cut the
word segments from the speech sentence. Figure-9 shows that
6 (six) black boxes represent 6 (six) word segments in the
speech sentence ‘আমাদের জাতীয় কবি কাজী নজরুল ইসলাম’.
Figure9. 6 (six) detected word segments in the speech
sentence „আমাদের জাতীয় কবি কাজী নজরুল ইসলাম‟.
6. EXPERIMENTAL RESULTS
The proposed system has been implemented in Windows
environment. All the methods and algorithms, discussed in
this paper, have been implemented in MATLAB 7.12.0
(R2011a) version. For the experiments there were compared 3
types of segmentation algorithms: k-means, fuzzy c-means
clustering and otsu‟s thresholding method. To evaluate the
performance of the proposed methods, different experiments
were carried out. In our experiments, various speech sentences
in Bangla language have been recorded, analyzed and
segmented by the proposed method. Table-1 shows the details
segmentation results for ten Bangla speech sentences and
reveals that the average segmentation accuracy rates are
94.11%; and 95.55% for k-means, 96.19% for FCM clustering
algorithms, and 90.58% for Otsu‟s method.
Table1. The details segmentation results
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7. CONCLUSIONS AND FURTHER RESEARCH
We have proposed three efficient methods for continuous
Bangla speech segmentation: two of them are usually used in
pattern classification (i.e., k-means and fuzzy c-means
clustering) and one of them is used in image segmentation
(i.e., Otsu‟s thresholding method). We also used new
approaches blocking black area and boundary detection
methods to properly detect word boundaries. From the
experimental results it is concluded that K-Means and FCM
clustering methods produce better segmentation results than
that of Otsu‟s Method. It was observed that some of the words
were not properly segmented, this is due to different causes:
(i) the utterance of words differs depending on their position
in the sentence; (ii) the pauses between the words are not
identical in all causes; and (iii) the non-uniform articulation of
speech. Also, the speech signal is very much sensitive to the
properties of speaker and environments. Experimental results
showed that the proposed approach is effective in continuous
speech segmentation. The major goal of future research is to
search a mechanism that can be employed to enable pattern
discovery by learning. We have a continuous effort to develop
a continuous speech recognition system using neuro-fuzzy
system.
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BIOGRAPHIES
Mr. Md. Mijanur Rahman is working as
Assistant Professor of the Dept. of
Computer Science and Engineering at
Jatiya Kabi Kazi Nazrul Islam University,
Trishal, Mymensingh, Bangladesh. Mr.
Rahman obtained his B. Sc. (Hons) and M.
Sc degrees, both with first class first in
Computer Science and Engineering from Islamic University,
Kushtia, Bangladesh. Now he is continuing his PhD program
in the department of Computer Science and Engineering at
Jahangirnagar University, Savar, Dhaka, Bangladesh.
His teaching and research interest lies in the areas such as
Digital Speech Processing, Pattern Recognition, Neural
Networks, Fuzzy Logic, Artificial Intelligence, etc. He has got
many research articles published in both national and
international journals.
Dr. Md. Al-Amin Bhuiyan is serving as a
professor of the Dept. of Computer Science
and Engineering at Jahangirnagar
University, Savar, Dhaka, Bangladesh. Dr.
Bhuiyan obtained his B. Sc. (Hons) and M.
Sc degrees both with first class in Applied
Physics & Electronics from the University of Dhaka,
Bangladesh. He obtained his PhD degree in Information &
Communication Engineering from Osaka City University,
Japan.
His teaching and research interest lies in the areas such as
Image Processing, Computer Vision, Computer Graphics,
Pattern Recognition, Soft Computing, Artificial Intelligence,
Robotics, etc. He has got many articles published in both
national and international journals.