Abstract
Facial expression recognition/identification (FER) systems plays vital role in the field of biometrics. Localizing the facial components accurately is a challenging task in image analysis and computer vision. Accurate detection of face and facial components gives effective performance with classification of expressions. This paper proposes feature based facial recognition system using JAFFE and CK databases. 18 facial landmarks were located using Haar cascade classifier. The distances between 12 points were extracted as features. These features were classified using SVM and K-NN classifier and comparison based on accuracy and execution time is done. The proposed algorithm gives better performance.
Multi-View Algorithm for Face, Eyes and Eye State Detection in Human Image- S...IJERA Editor
For fatigue detection such as in the application of driver‟s fatigue monitoring system, the eye state analysis is one of the important and deciding steps to determine the fatigue of driver‟s eyes. In this study, algorithms for face detection, eye detection and eye state analysis have been studied and presented as well as an efficient algorithm for detection of face, eyes have been proposed. Firstly the efficient algorithm for face detection method has been presented which find the face area in the human images. Then, novel algorithms for detection of eye region and eye state are introduced. In this paper we propose a multi-view based eye state detection to determine the state of the eye. With the help of skin color model, the algorithm detects the face regions in an YCbCr color model. By applying the skin segmentation which normally separates the skin and non-skin pixels of the images, it detects the face regions of the image under various lighting and noise conditions. Then from these face regions, the eye regions are extracted within those extracted face regions. Our proposed algorithms are fast and robust as there is not pattern match.
Fully Automatic Facial Feature Point Detection Using Gabor Feature Based Boos...Yen Ho
This is a key paper : Fully Automatic Facial Feature Point Detection Using Gabor Feature Based Boosted Classifiers - face detection (100%) & feature extraction(93%) for expressionless faces
Multi Local Feature Selection Using Genetic Algorithm For Face IdentificationCSCJournals
Face recognition is a biometric authentication method that has become more significant and relevant in recent years. It is becoming a more mature technology that has been employed in many large scale systems such as Visa Information System, surveillance access control and multimedia search engine. Generally, there are three categories of approaches for recognition, namely global facial feature, local facial feature and hybrid feature. Although the global facial-based feature approach is the most researched area, this approach is still plagued with many difficulties and drawbacks due to factors such as face orientation, illumination, and the presence of foreign objects. This paper presents an improved offline face recognition algorithm based on a multi-local feature selection approach for grayscale images. The approach taken in this work consists of five stages, namely face detection, facial feature (eyes, nose and mouth) extraction, moment generation, facial feature classification and face identification. Subsequently, these stages were applied to 3065 images from three distinct facial databases, namely ORL, Yale and AR. The experimental results obtained have shown that recognition rates of more than 89% have been achieved as compared to other global-based features and local facial-based feature approaches. The results also revealed that the technique is robust and invariant to translation, orientation, and scaling.
Multi-View Algorithm for Face, Eyes and Eye State Detection in Human Image- S...IJERA Editor
For fatigue detection such as in the application of driver‟s fatigue monitoring system, the eye state analysis is one of the important and deciding steps to determine the fatigue of driver‟s eyes. In this study, algorithms for face detection, eye detection and eye state analysis have been studied and presented as well as an efficient algorithm for detection of face, eyes have been proposed. Firstly the efficient algorithm for face detection method has been presented which find the face area in the human images. Then, novel algorithms for detection of eye region and eye state are introduced. In this paper we propose a multi-view based eye state detection to determine the state of the eye. With the help of skin color model, the algorithm detects the face regions in an YCbCr color model. By applying the skin segmentation which normally separates the skin and non-skin pixels of the images, it detects the face regions of the image under various lighting and noise conditions. Then from these face regions, the eye regions are extracted within those extracted face regions. Our proposed algorithms are fast and robust as there is not pattern match.
Fully Automatic Facial Feature Point Detection Using Gabor Feature Based Boos...Yen Ho
This is a key paper : Fully Automatic Facial Feature Point Detection Using Gabor Feature Based Boosted Classifiers - face detection (100%) & feature extraction(93%) for expressionless faces
Multi Local Feature Selection Using Genetic Algorithm For Face IdentificationCSCJournals
Face recognition is a biometric authentication method that has become more significant and relevant in recent years. It is becoming a more mature technology that has been employed in many large scale systems such as Visa Information System, surveillance access control and multimedia search engine. Generally, there are three categories of approaches for recognition, namely global facial feature, local facial feature and hybrid feature. Although the global facial-based feature approach is the most researched area, this approach is still plagued with many difficulties and drawbacks due to factors such as face orientation, illumination, and the presence of foreign objects. This paper presents an improved offline face recognition algorithm based on a multi-local feature selection approach for grayscale images. The approach taken in this work consists of five stages, namely face detection, facial feature (eyes, nose and mouth) extraction, moment generation, facial feature classification and face identification. Subsequently, these stages were applied to 3065 images from three distinct facial databases, namely ORL, Yale and AR. The experimental results obtained have shown that recognition rates of more than 89% have been achieved as compared to other global-based features and local facial-based feature approaches. The results also revealed that the technique is robust and invariant to translation, orientation, and scaling.
Facial Feature Tracking under Varying Facial Expressions and Face Poses based...Yen Ho
This is the 2nd key paper: Facial Feature Tracking under Varying Facial Expressions and Face Poses based on Restricted Boltzmann Machines
For faces with expression
PARTIAL MATCHING FACE RECOGNITION METHOD FOR REHABILITATION NURSING ROBOTS BEDSIJCSES Journal
In order to establish face recognition system in rehabilitation nursing robots beds and achieve real-time
monitor the patient on the bed. We propose a face recognition method based on partial matching Hu
moments which apply for rehabilitation nursing robots beds. Firstly we using Haar classifier to detect
human faces automatically in dynamic video frames. Secondly we using Otsu threshold method to extract
facial features (eyebrows, eyes, mouth) in the face image and its Hu moments. Finally, we using Hu
moment feature set to achieve the automatic face recognition. Experimental results show that this method
can efficiently identify face in a dynamic video and it has high practical value (the accuracy rate is 91%
and the average recognition time is 4.3s).
FACIAL EXTRACTION AND LIP TRACKING USING FACIAL POINTSijcseit
Automatic facial feature extraction is one of the most important and attempted problems in computer
vision. It is a necessary step in face recognition, facial image compression. There are many methods have
been proposed in the literature for the facial feature extraction task. However, all of them have still
disadvantage such as not complete reflection about face structure, face texture. In this paper, we propose
a method for fast and accurate extraction of feature points such as eyes, nose, mouth, eyebrows and the
like from dynamic images with the purpose of face recognition. These methods are far from satisfactory
in terms of extraction accuracy and processing speed. The proposed method achieves high position
accuracy at a low computing cost by combining shape extraction with geometric features of facial images
like eyes, nose, mouth etc. In this paper, a facial expressions synthesis system, based on the facial points
tracking in the frontal image sequences. Selected facial points are automatically tracked using a crosscorrelation based optical flow. The proposed synthesis system uses a simple facial features model with a
few set of control points that can be tracked in original facial image sequences.
Driver's drowsiness is one of the major causes of serious accidents in road traffic. Thus, special effort in searching for better assistant technology has been paid. However, several existing approaches fail to work effectively as the head of a drowsy driver is usually in slanting state. Moreover, the shaking of vehicle or the driver's winking even makes the problem much more complicated. Anyway, head bend posture also signifies a drowsy state. Consequently, this paper proposes a novel approach by considering head nodding behavior as an input in our detection model. After detecting a human face, some significant facial features are extracted; then, they are used to calculate the predetermined optimal parameters; finally, drowsiness is
evaluated based on these thresholds. In our empirical experiments, the proposed algorithm can successfully
and accurately detect 96.56% of cases.
Driver’s drowsiness is one of the major causes of serious accidents in road traffic. Thus, special effort in searching for better assistant technology has been paid. However, several existing approaches fail to work effectively as the head of a drowsy driver is usually in slanting state. Moreover, the shaking of vehicle or the driver’s winking even makes the problem much more complicated. Anyway, head bend posture also signifies a drowsy state. Consequently, this paper proposes a novel approach by considering head nodding behaviour as an input in our detection model. After detecting a human face, some significant facial features are extracted; then, they are used to calculate the predetermined optimal parameters; finally, drowsiness is evaluated based on these thresholds. In our empirical experiments, the proposed algorithm can successfully and accurately detect 96.56% of cases.
Comparative Study of Lip Extraction Feature with Eye Feature Extraction Algor...Editor IJCATR
In recent time, along with the advances and new inventions in science and technology, fraud people and identity thieves are
also becoming smarter by finding new ways to fool the authorization and authentication process. So, there is a strong need of efficient
face recognition process or computer systems capable of recognizing faces of authenticated persons. One way to make face recognition
efficient is by extracting features of faces. This paper is to compare the relative efficiency of Lip Extraction and Eye extraction feature
for face recognition in biometric devices. Importance of this paper is to bring to the light which Feature Extraction method provides
better results under various conditions. For recognition experiments, I used face images of persons from different sets of YALE
database. In my dataset, there are total 132 images consisting of 11 persons & 12 face images of each person.
Automatic facial expression analysis is an area of great research especially in the field of computer vision and robotics. In the work done so far, the facial expression analysis is done either by recognizing the facial expression directly or indirectly by first recognizing AUs and then applying this information for facial expression analysis. The various challenges in facial expression analysis are associated with face detection and tracking, facial feature extraction and the facial feature classification. The presented review gives a brief description of the time line view of the research work carried for AU detection/estimation in static and dynamic image sequences and possible solutions proposed by researchers in this field since 2002. In short, the paper will provide an impetus for various challenges and applications of AU detection, and new research topics, which will increase the productivity in this exciting and challenging field.
This paper describes for a robust face recognition system using skin segmentation technique. This paper addresses the problem of detecting faces in color images in the presence of various lighting conditions. In this paper the face is preprocessed using histogram equalization to avoid illumination problems and then is detected using skin segmentation method. The principal component analysis using neural network is used to recognize the extracted facial features.
Implementation of face and eye detection on DM6437 board using simulink modeljournalBEEI
Driver Assistance system is significant in drriver drowsiness to avoid on road accidents. The aim of this research work is to detect the position of driver’s eye for fatigue estimation. It is not unusual to see vehicles moving around even during the nights. In such circumstances there will be very high probability that a driver gets drowsy which may lead to fatal accidents. Providing a solution to this problem has become a motivating factor for this research, which aims at detecting driver fatigue. This research concentrates on locating the eye region failing which a warning signal is generated so as to alert the driver. In this paper, an efficient algorithm is proposed for detecting the location of an eye, which forms an invaluable insight for driver fatigue detection after the face detection stage. After detecting the eyes, eye tracking for input videos has to be achieved so that the blink rate of eyes can be determined.
Vakola, M., Nikolaou, I., & Bourantas, D. (2004). The Role of Organizational Silence on Employees’ Trust and Attitudes in a Post Merger-Stage. Annual Meeting of the Academy of Management, New Orleans.
Via Lorelei Lingard: In an effort to convey research results a little differently, I created the following 'short story', to be performed in silence, at the HRS Graduate Research Day at UWO on February 9th. I thought it would be neat, and symbolic, to delivery a silent talk on the topic of "Silence" in team communication research. I learned two things: 1) It's hard to create slides that say it all, without verbal transition material spoken within and between them, and 2) It's a bit nerve-wracking to present a talk and stay perfectly silent while it unfolds.
Facial Feature Tracking under Varying Facial Expressions and Face Poses based...Yen Ho
This is the 2nd key paper: Facial Feature Tracking under Varying Facial Expressions and Face Poses based on Restricted Boltzmann Machines
For faces with expression
PARTIAL MATCHING FACE RECOGNITION METHOD FOR REHABILITATION NURSING ROBOTS BEDSIJCSES Journal
In order to establish face recognition system in rehabilitation nursing robots beds and achieve real-time
monitor the patient on the bed. We propose a face recognition method based on partial matching Hu
moments which apply for rehabilitation nursing robots beds. Firstly we using Haar classifier to detect
human faces automatically in dynamic video frames. Secondly we using Otsu threshold method to extract
facial features (eyebrows, eyes, mouth) in the face image and its Hu moments. Finally, we using Hu
moment feature set to achieve the automatic face recognition. Experimental results show that this method
can efficiently identify face in a dynamic video and it has high practical value (the accuracy rate is 91%
and the average recognition time is 4.3s).
FACIAL EXTRACTION AND LIP TRACKING USING FACIAL POINTSijcseit
Automatic facial feature extraction is one of the most important and attempted problems in computer
vision. It is a necessary step in face recognition, facial image compression. There are many methods have
been proposed in the literature for the facial feature extraction task. However, all of them have still
disadvantage such as not complete reflection about face structure, face texture. In this paper, we propose
a method for fast and accurate extraction of feature points such as eyes, nose, mouth, eyebrows and the
like from dynamic images with the purpose of face recognition. These methods are far from satisfactory
in terms of extraction accuracy and processing speed. The proposed method achieves high position
accuracy at a low computing cost by combining shape extraction with geometric features of facial images
like eyes, nose, mouth etc. In this paper, a facial expressions synthesis system, based on the facial points
tracking in the frontal image sequences. Selected facial points are automatically tracked using a crosscorrelation based optical flow. The proposed synthesis system uses a simple facial features model with a
few set of control points that can be tracked in original facial image sequences.
Driver's drowsiness is one of the major causes of serious accidents in road traffic. Thus, special effort in searching for better assistant technology has been paid. However, several existing approaches fail to work effectively as the head of a drowsy driver is usually in slanting state. Moreover, the shaking of vehicle or the driver's winking even makes the problem much more complicated. Anyway, head bend posture also signifies a drowsy state. Consequently, this paper proposes a novel approach by considering head nodding behavior as an input in our detection model. After detecting a human face, some significant facial features are extracted; then, they are used to calculate the predetermined optimal parameters; finally, drowsiness is
evaluated based on these thresholds. In our empirical experiments, the proposed algorithm can successfully
and accurately detect 96.56% of cases.
Driver’s drowsiness is one of the major causes of serious accidents in road traffic. Thus, special effort in searching for better assistant technology has been paid. However, several existing approaches fail to work effectively as the head of a drowsy driver is usually in slanting state. Moreover, the shaking of vehicle or the driver’s winking even makes the problem much more complicated. Anyway, head bend posture also signifies a drowsy state. Consequently, this paper proposes a novel approach by considering head nodding behaviour as an input in our detection model. After detecting a human face, some significant facial features are extracted; then, they are used to calculate the predetermined optimal parameters; finally, drowsiness is evaluated based on these thresholds. In our empirical experiments, the proposed algorithm can successfully and accurately detect 96.56% of cases.
Comparative Study of Lip Extraction Feature with Eye Feature Extraction Algor...Editor IJCATR
In recent time, along with the advances and new inventions in science and technology, fraud people and identity thieves are
also becoming smarter by finding new ways to fool the authorization and authentication process. So, there is a strong need of efficient
face recognition process or computer systems capable of recognizing faces of authenticated persons. One way to make face recognition
efficient is by extracting features of faces. This paper is to compare the relative efficiency of Lip Extraction and Eye extraction feature
for face recognition in biometric devices. Importance of this paper is to bring to the light which Feature Extraction method provides
better results under various conditions. For recognition experiments, I used face images of persons from different sets of YALE
database. In my dataset, there are total 132 images consisting of 11 persons & 12 face images of each person.
Automatic facial expression analysis is an area of great research especially in the field of computer vision and robotics. In the work done so far, the facial expression analysis is done either by recognizing the facial expression directly or indirectly by first recognizing AUs and then applying this information for facial expression analysis. The various challenges in facial expression analysis are associated with face detection and tracking, facial feature extraction and the facial feature classification. The presented review gives a brief description of the time line view of the research work carried for AU detection/estimation in static and dynamic image sequences and possible solutions proposed by researchers in this field since 2002. In short, the paper will provide an impetus for various challenges and applications of AU detection, and new research topics, which will increase the productivity in this exciting and challenging field.
This paper describes for a robust face recognition system using skin segmentation technique. This paper addresses the problem of detecting faces in color images in the presence of various lighting conditions. In this paper the face is preprocessed using histogram equalization to avoid illumination problems and then is detected using skin segmentation method. The principal component analysis using neural network is used to recognize the extracted facial features.
Implementation of face and eye detection on DM6437 board using simulink modeljournalBEEI
Driver Assistance system is significant in drriver drowsiness to avoid on road accidents. The aim of this research work is to detect the position of driver’s eye for fatigue estimation. It is not unusual to see vehicles moving around even during the nights. In such circumstances there will be very high probability that a driver gets drowsy which may lead to fatal accidents. Providing a solution to this problem has become a motivating factor for this research, which aims at detecting driver fatigue. This research concentrates on locating the eye region failing which a warning signal is generated so as to alert the driver. In this paper, an efficient algorithm is proposed for detecting the location of an eye, which forms an invaluable insight for driver fatigue detection after the face detection stage. After detecting the eyes, eye tracking for input videos has to be achieved so that the blink rate of eyes can be determined.
Vakola, M., Nikolaou, I., & Bourantas, D. (2004). The Role of Organizational Silence on Employees’ Trust and Attitudes in a Post Merger-Stage. Annual Meeting of the Academy of Management, New Orleans.
Via Lorelei Lingard: In an effort to convey research results a little differently, I created the following 'short story', to be performed in silence, at the HRS Graduate Research Day at UWO on February 9th. I thought it would be neat, and symbolic, to delivery a silent talk on the topic of "Silence" in team communication research. I learned two things: 1) It's hard to create slides that say it all, without verbal transition material spoken within and between them, and 2) It's a bit nerve-wracking to present a talk and stay perfectly silent while it unfolds.
A study of techniques for facial detection and expression classificationIJCSES Journal
Automatic recognition of facial expressions is an important component for human-machine interfaces. It
has lot of attraction in research area since 1990's.Although humans recognize face without effort or
delay, recognition by a machine is still a challenge. Some of its challenges are highly dynamic in their
orientation, lightening, scale, facial expression and occlusion. Applications are in the fields like user
authentication, person identification, video surveillance, information security, data privacy etc. The
various approaches for facial recognition are categorized into two namely holistic based facial
recognition and feature based facial recognition. Holistic based treat the image data as one entity without
isolating different region in the face where as feature based methods identify certain points on the face
such as eyes, nose and mouth etc. In this paper, facial expression recognition is analyzed with various
methods of facial detection,facial feature extraction and classification.
A Spectral Domain Local Feature Extraction Algorithm for Face RecognitionCSCJournals
In this paper, a spectral domain feature extraction algorithm for face recognition is proposed, which efficiently exploits the local spatial variations in a face image. For the purpose of feature extraction, instead of considering the entire face image, an entropy-based local band selection criterion is developed, which selects high-informative horizontal bands from the face image. In order to capture the local variations within these high-informative horizontal bands precisely, a feature selection algorithm based on two-dimensional discrete Fourier transform (2D-DFT) is proposed. Magnitudes corresponding to the dominant 2D-DFT coefficients are selected as features and shown to provide high within-class compactness and high between-class separability. A principal component analysis is performed to further reduce the dimensionality of the feature space. Extensive experimentations have been carried out upon standard face databases and the recognition performance is compared with some of the existing face recognition schemes. It is found that the proposed method offers not only computational savings but also a very high degree of recognition accuracy.
REVIEW OF FACE DETECTION SYSTEMS BASED ARTIFICIAL NEURAL NETWORKS ALGORITHMSijma
Face detection is one of the most relevant applications of image processing and biometric systems.
Artificial neural networks (ANN) have been used in the field of image processing and pattern recognition.
There is lack of literature surveys which give overview about the studies and researches related to the using
of ANN in face detection. Therefore, this research includes a general review of face detection studies and
systems which based on different ANN approaches and algorithms. The strengths and limitations of these
literature studies and systems were included also.
Review of face detection systems based artificial neural networks algorithmsijma
Face detection is one of the most relevant applications of image processing and biometric systems.
Artificial neural networks (ANN) have been used in the field of image processing and pattern recognition.
There is lack of literature surveys which give overview about the studies and researches related to the using
of ANN in face detection. Therefore, this research includes a general review of face detection studies and
systems which based on different ANN approaches and algorithms. The strengths and limitations of these
literature studies and systems were included also.
Research and Development of DSP-Based Face Recognition System for Robotic Reh...IJCSES Journal
This article describes the development of DSP as the core of the face recognition system, on the basis of
understanding the background, significance and current research situation at home and abroad of face
recognition issue, having a in-depth study to face detection, Image preprocessing, feature extraction face
facial structure, facial expression feature extraction, classification and other issues during face recognition
and have achieved research and development of DSP-based face recognition system for robotic
rehabilitation nursing beds. The system uses a fixed-point DSP TMS320DM642 as a central processing
unit, with a strong processing performance, high flexibility and programmability.
Facial Expression Recognition Based on Facial Motion Patternsijeei-iaes
Facial expression is one of the most powerful and direct mediums embedded in human beings to communicate with other individuals’ feelings and abilities. In recent years, many surveys have been carried on facial expression analysis. With developments in machine vision and artificial intelligence, facial expression recognition is considered a key technique of the developments in computer interaction of mankind and is applied in the natural interaction between human and computer, machine vision and psycho- medical therapy. In this paper, we have developed a new method to recognize facial expressions based on discovering differences of facial expressions, and consequently appointed a unique pattern to each single expression.by analyzing the image by means of a neighboring window on it, this recognition system is locally estimated. The features are extracted as binary local features; and according to changes in points of windows, facial points get a directional motion per each facial expression. Using pointy motion of all facial expressions and stablishing a ranking system, we delete additional motion points that decrease and increase, respectively, the ranking size and strenghth. Classification is provided according to the nearest neighbor. In the conclusion of the paper, the results obtained from the experiments on tatal data of Cohn-Kanade demonstrate that our proposed algorithm, compared to previous methods (hierarchical algorithm combined with several features and morphological methods as well as geometrical algorithms), has a better performance and higher reliability.
Facial Expression Recognition Using Local Binary Pattern and Support Vector M...AM Publications
Facial expression analysis is a remarkable and demanding problem, and impacts significant applications in various fields like human-computer interaction and data-driven animation. Developing an efficient facial representation from the original face images is a crucial step for achieving facial expression recognition. Facial representation based on statistical local features, Local Binary Patterns (LBP) is practically assessed. Several machine learning techniques were thoroughly observed on various databases. LBP features- which are effectual and competent for facial expression recognition are generally used by researchers Cohn Kanade is the database for present work and the programming language used is MATLAB. Firstly, face area is divided in small regions, by which histograms, Local Binary Patterns (LBP) are extracted and then concatenated into single feature vector. This feature vector outlines a well-organized representation of face and is helpful in determining the resemblance among images.
Facial Expression Recognition Using Local Binary Pattern and Support Vector M...AM Publications
Facial expression analysis is a remarkable and demanding problem, and impacts significant applications in various fields like human-computer interaction and data-driven animation. Developing an efficient facial representation from the original face images is a crucial step for achieving facial expression recognition. Facial representation based on statistical local features, Local Binary Patterns (LBP) is practically assessed. Several machine learning techniques were thoroughly observed on various databases. LBP features- which are effectual and competent for facial expression recognition are generally used by researchers Cohn Kanade is the database for present work and the programming language used is MATLAB. Firstly, face area is divided in small regions, by which histograms, Local Binary Patterns (LBP) are extracted and then concatenated into single feature vector. This feature vector outlines a well-organized representation of face and is helpful in determining the resemblance among images.
Fiducial Point Location Algorithm for Automatic Facial Expression Recognitionijtsrd
We present an algorithm for the automatic recognition of facial features for color images of either frontal or rotated human faces. The algorithm first identifies the sub images containing each feature, afterwards, it processes them separately to extract the characteristic fiducial points. Then Calculate the Euclidean distances between the center of gravity coordinate and the annotated fiducial points coordinates of the face image. A system that performs these operations accurately and in real time would form a big step in achieving a human like interaction between man and machine. This paper surveys the past work in solving these problems. The features are looked for in down sampled images, the fiducial points are identified in the high resolution ones. Experiments indicate that our proposed method can obtain good classification accuracy. D. Malathi | A. Mathangopi | Dr. D. Rajinigirinath ""Fiducial Point Location Algorithm for Automatic Facial Expression Recognition"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21754.pdf
Paper URL: https://www.ijtsrd.com/computer-science/data-miining/21754/fiducial-point-location-algorithm-for-automatic-facial-expression-recognition/d-malathi
Similar to Facial expression identification by using features of salient facial landmarks (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.
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.
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.
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.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
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.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
block diagram and signal flow graph representation
Facial expression identification by using features of salient facial landmarks
1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
FACIAL EXPRESSION IDENTIFICATION BY USING FEATURES OF
SALIENT FACIAL LANDMARKS
Abhilasha Shukla1
, D. D. Dighe2
1
Department of Electronics and Telecommunication, Savitribai Phule Pune University, India
2
Department of Electronics and Telecommunication, Savitribai Phule Pune University, India
Abstract
Facial expression recognition/identification (FER) systems plays vital role in the field of biometrics. Localizing the facial
components accurately is a challenging task in image analysis and computer vision. Accurate detection of face and facial
components gives effective performance with classification of expressions. This paper proposes feature based facial recognition
system using JAFFE and CK databases. 18 facial landmarks were located using Haar cascade classifier. The distances between
12 points were extracted as features. These features were classified using SVM and K-NN classifier and comparison based on
accuracy and execution time is done. The proposed algorithm gives better performance.
Keywords: Facial expression recognition (FER) system, Face detection, Feature extraction, Expression classification
--------------------------------------------------------------------
***----------------------------------------------------------------------
1. INTRODUCTION
Fundamental modes of communicating human emotions are
facial expressions. Facial expression, body language,
expressive features of speech, physiological signals (e.g.
EMG, ECG, EOG, EEG, FMRI, etc.) are some rare
examples of signals that are beneficial for identification
purpose. The detection of six universal expressions like
happiness, sadness, anger, fear, disgust and surprise is the
base of the research on facial expression analysis. Since the
last few decades, a number of facial expression
identification techniques have been proposed. For effective
expression analysis, dependencies are based upon the
accurate representation of facial features. Using this feature
we have several usages in the realm of human-computer
interaction (HCI), like social signal processing, social
robots, deceit detection, interactive video and behavior
monitoring.
Automatic FER systems consist of three major steps: Face
detection, Feature extraction and Facial expression
classification. Firstly, in any FER system face detection is
been done for detecting features like eyes, eyebrows, nose
and mouth which is further followed by extraction of
features. There are several methods used for feature
extraction purpose; but most of the present algorithms are
based on geometric and appearance based features. In
geometric-based method the layout of the face and facial
components is being tracked like eyes, eyebrows, nose,
mouth (lip corners) etc., and classify the expressions based
on the relative location of these facial features. Some
researcher categories the facial expression using shape
model. In many practical situations, it is difficult to achieve
tracking of facial landmarks, and for that these methods
usually require exact and reliable detection. The Euclidean
distance between facial features keeps varying with the
people, thereby making the person independent expression
identification less reliable. To overcome this appearance-
based method can be applied which involves distinct filters
such as Gabor, Wavelets, and LBP etc. These are implied on
either entire face or at the précised part of it to encode the
texture. PCA, ICA, LDA etc, are certain dimensionality
reduction methods which are used in appearance based as in
this high dimensional vectors are generated which further
has to be delineated in lower dimensional subspace.
Lastly expression classification is performed in the learned
subspace. Many researchers state that accurate extraction of
features can be achieved by dividing the face into several
components. But this approach fails with inappropriate face
arrangement and occlusions. Based on training data, features
from certain facial parts, mostly determined facial parts that
contribute more towards expression discrimination. And the
positions and sizes of the facial landmarks are differing in
this kind of approaches, making it difficult to conceive a
generic system.
2. RELATED WORKS
To increase the performance of facial expression
identification it is very important to correctly detect the
facial elements which are followed by feature extraction and
classification of expressions. Pantic and Rothkrantz [1] used
the geometric approach model based method in which 19
_______________________________________________________________________________________________
Volume: 05 Issue: 08 | Aug-2016, Available @ http://ijret.esatjournals.org 57
2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
points from frontal view and 10 points from profile view
were used to describe the face model. The frontal and profile
combination has enhanced the face model quality. Hammal
[2] used the contour-based approach in which contours of
facial features are been automatically extracted. Its major
disadvantage is confusion errors arose between distinct
facial expression classes. In [3] Black and Yacoob proposed
a new approach using optical flow-based method in which
facial expressions were detected from motion temporal
video information.
These were the few geometric approach based methods [1],
[2], [3], [4] where facial landmarks were detected by using
the parametric geometric model. Some appearance based
approach [5] Sirovich and Kirby used the Principal
component analysis (PCA) also known as eigenface
approach is widely used as reducing the dimensionality.
Belhumeur [6] used FLD Fishers linear discriminant whose
error rate is lower and recognition rate is more than PCA.
Author [7] applied eigenface based algorithm to various
images clicked under peculiar illuminations and
backgrounds, where the size of an image is 180*200 and
required durations is 4.5456 sec.
In Zhang’s work [8] the facial images are pre-processed and
then the evaluation is done separately with different Gabor
filters where these filters are functioned separately on
different expression. The classifier assumes the discriminate
function to be a linear function of the feature data. In this
case the data is the feature vector obtained. Its advantage is
reduction in dimension of feature space and computation
complexity. In Shan’s proposed work [9] analytic local
features represent face, LBP is used for person sovereign
expressions identification in which texture analysis is done
using SVM.
In this paper we [1] proposed here a novel salient facial
landmark detection technique based facial expression
recognition framework, which gives significant performance
at different image resolutions.
A multi-class classifier classifies the images into six basic
expression classes. And it uses lower computational
complexity to perform the state-of-art methods in near
frontal images. To reduce the computation, the appearance
features with lower number of histogram bins are used.
3. PROPOSED ALGORITHM
3.1 System Block Diagram
Facial expression involves the facial muscles contraction
and expansion. The proposed facial expression recognition
system is explained below-
3.2 Image Acquisition and Pre-processing
Facial expression images are gathered from the different
databases such as JAFFE, Cohn-Kanade etc. JAFFE
database consist of the image of different seven expressions
of different Japanese female. The input image contains some
distortion. To remove distortion and to get smoothen
images; we applied the Gaussian filter of kernel size 5×5. In
similar way CK database consist of images from 100
different universities from 18 to 30 years of age group.
Image sequences from normal to target display were
digitized into 640*490 pixels with 8bit precision for gray
scale values.
3.3 Facial Landmark Detection
Facial part detection is important step to detect facial
landmark and emotion recognition. To detect face and facial
part Haar cascade classifier is used. The general object
detector framework is proposed by Viola and Jones in 2004.
It is mainly based on the basis of boosting cascade of weak
classifiers. It trains the separate classifier for each target
object and rejects non-object patterns. By using Haar
cascade classifier, we detect left and right eyes, Nose,
Mouth.
3.3.1 Eyes, Nose and Mouth Detection
The facial image is given to the Haar cascade classifier to
detect both the eyes separately. Haar cascade classifier
returns the vertices(x, y, w, h) of the eye position. By using
Haar cascade classifier we can reduce the computational
complexity of the algorithm. In similar manner, we can
detect Nose as well as Mouth from the facial image.
Algorithm
1.Select the coarse ROI for eyes and nose
2.Detection of eyes using Haar Classifier which is trained
separately for both the eyes
3.Center of eyes were computed using the coordinates of
vertices which were provided by Haar classifier
4.Localization of nose and mouth in similar way that of
eyes using Haar cascade
5.Localization of eyes was made using up-right face
alignment as position of eyes do not change with
expressions.
3.3.2 Lips and Eyebrows Corner Detection
Once the mouth is detected, we can extract the lip corners
likewise with prior to eyebrow ROI, we can detect eyebrow
corner. The upper lip and eyebrow produce the edge. It can
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be detected by the horizontal Sobel edge detector. The
detailed process is shown in below flowchart Fig-2.
Fig-1 System Block Diagram
Fig-2: Flowchart for Lip corner and Eyebrow corner
detection Algorithm
3.4 Facial Landmark Extraction
During different facial expression different facial points are
active. So we need to detect such a facial points from the
facial image and corresponding position of different facial
part. The detailed active facial points are shown in below
fig.3. As shown below in Fig-3, the 18 landmark points (L1-
L18) were localized using which 12 features were extracted
whose selection is explained later in this paper.
Fig-3: Position of facial landmarks.
3.5 Selection of Features
The different facial expression involves a different pair of
facial landmarks, e.g. for Happy, the lip corner distance(L5-
L6 & L17-L18) getting increased as well as distance
between cheek point(L12-L13) and eye center(L8-L9) get
decreased. Below Table-1 described the facial expressions
and involve facial points.
Table 1: Facial Expressions and Involved Facial points
Expressions Involved facial Landmark Points
ANGER L5,L6,L17,L18
DISGUST L5, L6, L8, L9, L2, L13, L14, L15,
L18
FEAR L1, L4, L5, L6, L8, L9, L14, L15,
L17, L18
HAPPY L5, L6, L8, L9, L12, L13, L16, L17,
L18
NORMAL None
SAD L16, L17, L18
SURPRISE L5, L6, L7, L8, L9, L11, L12, L13,
L15, L16, L17, L18
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Different facial expressions involve some common
landmarks. So we need to optimize those landmarks. After
optimizing the landmarks 6 horizontal distance and 6
vertical distance feature were obtained. Final feature
selection is tabulated below in Table-2.
Table 2: Final Feature Selection
Horizontal Distances Vertical distances
1.A1(q)=L16(1)-L5(1),
2.A2(q)= L16(1)-L17(1),
3.A3(q)=L6(1)-L16(1),
4. A4(q) = L11(1)-L4(1);
5.A5(q)=L11(1)-L1(1),
6. A6(q) = L18(1)-L16(1)
7.A7(q)=L12(2)-L8(2),
8.A8(q)=L14(2)-L8(2),
9.A9(q)=L15(2)-L9(2),
10.A10(q)=L13(2)-L9(2),
11.A11(q)=L8(2)-L14(2),
12.A12(q)=L9(2) - L15(2)
3.6 Classification
Classification is the process of classifying the unknown
input data into respective classes. We used multiclass
support vector machine (SVM) and K-NN for classification
of facial expression into 7 groups such as anger, disgust,
fear, happy, normal, sad and surprised.
3.6.1 SVM
SVM is first developed by Vapnik [12] and the learner. The
input image to the SVM classifier is the feature vectors
which are generated during the training phase. The
classification of this trained data in the given feature space
is done by using hyperplane concept defined by the type of
kernel function used. Here the SVM classifier uses the RBF
(Radial Basis Function) type of kernel which provides better
accuracy as compared to linear and polynomial based
classifiers.
The classification of data in high dimensional feature space
is based on algebra and geometry with its non-linear rules in
the input space. For this purpose the learning algorithm is
formulated by using kernel function (RBF) which allows
efficient computation of the trained vectors. Using the
nonlinear mapping that embeds input vectors into feature
space, kernel has the form-
(1)
The separation of trained database is based on hyperplane
defined by the type of kernel used. The hyperplane of
maximal margin is defined as the sum of the distances of the
hyperplane defined by the type of kernel used. The
hyperplane of the maximal margin is defined as the sum of
the distances of the hyperplane from the nearest data point
of each of the two classes. The SVM methodology learns
non-linear functions of the form-
(2)
Where, is the lagranges multipliers of a dual optimization
problem, it is to show that are non-zero in the optimal
solution which are arising from the training points nearest to
the hyperplane called as support vectors.
3.6.2 KNN
KNN algorithm (K-Nearest Neighbor) is a non-parametric
tool generally used for pattern recognition. It is used for
both the purpose i.e. classification and regression
respectively; in which the input contains the nearest value
(weight) of K training examples in the feature space.
The classification is based on majority vote of its neighbors,
with the object being assigned to the class most common
among its K nearest neighbor, where K is considered as
positive integer. This choice of K being positive is based
upon the data; it is considered that larger the value of K
lesser is the interference of noise while classification. The
algorithm for K-NN is shown below in the Fig-4.
Fig-4: K-NN Flowchart
4. PERFORMANCE ANALYSIS
In the proposed approach,18 landmark points were localized
i.e. L1-L18 using Viola-Jones algorithm with HAAR
cascade like features with the input as 63 facial images of
different expressions from JAFFE database and 54 facial
images from CK database. While training, by using those 18
landmark points 12 features (A1-A12) were extracted in
which 6 (A1-A6) are horizontal features and rest 6 (A7-
A12) are vertical. As explained previously in this paper the
feature extraction phase is been carried out by using
landmark detection algorithm which is based on Euclidean
distance method. The selection of features is purely based
practical analysis. Later for testing 35 images (5 images for
each expression) from both the databases were taken and
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5. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
classification was done by using two classifiers i.e. SVM
and K-NN. Hence this section includes comparison of
performance of both the classifiers and databases by
considering the parameters like accuracy and execution
time.
4.1 Qualitative Analysis
Qualitative measurement focuses on collecting information
that is not numerical. The output of the proposed system at
different stages are shown below in Fig-5
4.1.1 Localization of 18 Landmark Points L1-L8
(a)JAFFE (b) Cohn- Kanade
Fig-5: (a) JAFFE and (b) Cohn-Kanade Database Labeled
Facial Landmark Points L1-L18.
4.1.2 Extraction of Features for both the Databases
and Storing the Feature Vector in Excel (.xls) File
(a)
(b)
Fig-6: (a) Feature Vectors of 63 images from JAFFE
Database, (b) Feature Vectors of 54 images from CK
Database
4.1.3 Expression Classification
Below Table-3 shows the final expression classification
done by using the SVM and K-NN classifier. The extracted
feature vectors during testing are compared with the
previously stored vectors during training phase. Comparison
is done using SVM’s hyper plane and K-nearest neighbor
concept on the basis of which image is been classified and
hence we get the final result.
Table-3: Expression Classification by using SVM and K-
NN Classifier
(a) JAFFE
(b) CK (c) SVM Output
(a) JAFFE
(b) CK (c) K-NN Output
4.2 Quantitative Analysis
For quantitative analysis 35 images from JAFFE and CK
database 5 images from each class, were given as input to
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SVM and K-NN classifier to measure the accuracy and
execution time of classification. Table-4 shows the
comparison made between two classifiers SVM and K-NN
using CK and JAFFE databases. The comparison is based on
expression recognition accuracy which is plotted in the
below graph i.e. represented in the Chart-1. The comparison
made by considering execution time is also shown in Table-
5 and Chart-2 respectively.
Table-4: Comparison based on expression recognition
accuracy
SVM K-NN
JAFFE 82.85% 65.71%
CK 93.30% 80%
Chart-1: Comparison graph plotted, based on accuracy
Table.5. Comparison based on accuracy and time
Accuracy
(%)
Time
(sec)
JAFFE+SVM 82.86 11.963
JAFFE+K-NN 65.71 12.209
CK+SVM 88.57 14.101
CK+K-NN 80 12.547
Chart-2: Comparison graph plotted, based on accuracy and
time
In the above analysis 35 images from both the databases
were tested separately which includes 5 images from each
class i.e. anger, disgust, fear, happy, neutral, sad and
surprise using SVM and K-NN classifier respectively. The
accuracy of expression recognition for SVM+JAFFE is
82.86% and execution time required by it is 11.963sec;
likewise for SVM+CK is 65.71% and time required is
12.209sec, CK+JAFFE is 88.57% and time required is
14.101sec and lastly CK+K-NN is 80% and time required
by it is 12.547sec respectively.
5. CONCLUSION
The proposed system presents the computationally efficient
FER system which accurately classifies the 7 universal
facial expression classes. All the majorly active regions on
the face which are responsible during the formation of
expressions are extracted using landmark detection
technique. These 12 features are extracted using previously
located 18 landmark points. These 18 points are determined
from the salient areas of the face where the features are
discriminative for different expressions. Following with the
classification using SVM and K-NN classifier, comparison
using the parameters like expression recognition accuracy
and execution time is done. This shows that the computation
is better in the SVM classifier than the traditional K-NN
algorithm, and also the performance is stable for any type of
database used.
ACKNOWLEDGEMENT
I take this opportunity to express my sincere gratitude to my
guide, Mr. D. D. Dighe, for his constant encouragement,
wonderful technical guidance and support throughout my
work. I sincerely thank Prof. S. D. Pable of Electronics &
Telecommunication Department for his advice and support
during course of this work. I express my thanks to all
teaching & non- teaching staff of Electronics &
Telecommunication Department for their kind cooperation
and guidance for preparing and presenting this paper. I take
this opportunity to express my gratitude towards my parents
and my friends without whom it would have not been
possible.
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