To achieve a natural interaction in augmented reality environment, we have suggested to use markerless visionbased two-handed gestures for the interaction; with an outstretched hand and a pointing hand used as virtual object registration plane and pointing device respectively. However, twohanded interaction always causes mutual occlusion which jeopardizes the hand gesture recognition. In this paper, we present a solution for two-hand occlusion by using watershed transform. The main idea is to start from a two-hand occlusion image in binary format, then form a grey-scale image based on the distance of each non-object pixel to object pixel. The watershed algorithm is applied to the negation of the grey scaled image to form watershed lines which separate the two hands. Fingertips are then identified and each hand is recognized based on the number of fingertips on each hand. The outstretched hand is assumed to contain 5 fingertips and the pointing device contains less than 5 fingertips. An example of applying our result in hand and virtual object interaction is displayed at the end of the paper.
Hand gesture classification is popularly used in
wide applications like Human-Machine Interface, Virtual
Reality, Sign Language Recognition, Animations etc. The
classification accuracy of static gestures depends on the
technique used to extract the features as well as the classifier
used in the system. To achieve the invariance to illumination
against complex background, experimentation has been
carried out to generate a feature vector based on skin color
detection by fusing the Fourier descriptors of the image with
its geometrical features. Such feature vectors are then used in
Neural Network environment implementing Back
Propagation algorithm to classify the hand gestures. The set
of images for the hand gestures used in the proposed research
work are collected from the standard databases viz.
Sebastien Marcel Database, Cambridge Hand Gesture Data
set and NUS Hand Posture dataset. An average classification
accuracy of 95.25% has been observed which is on par with
that reported in the literature by the earlier researchers.
Gesture Recognition Review: A Survey of Various Gesture Recognition AlgorithmsIJRES Journal
This paper presents simple as well as effective methods to realize hand gesture recognition. Gesture recognition is mainly apprehensive on analysing the functionality of human Intelligence. The main aim of gesture detection and recognition is to design an efficient system which is able to recognize particular human gestures and use these detected gestures to transfer information or for controlling devices. Hand gestures enable a vivid complementary modal to communicate with speech for expressing ones thought of idea. The information which is associated with hand gestures detection in a conversation is extent or degree, detection discourse structure, spatial and temporal design structure. Based on the above given points the paper discusses various models of gesture detection and recognition.
This paper presents the maneuver of mouse pointer and performs various mouse operations such as left
click, right click, double click, drag etc using gestures recognition technique. Recognizing gestures is a
complex task which involves many aspects such as motion modeling, motion analysis, pattern recognition
and machine learning.
Keeping all the essential factors in mind a system has been created which recognizes the movement of
fingers and various patterns formed by them. Color caps have been used for fingers to distinguish it from
the background color such as skin color. Thus recognizing the gestures various mouse events have been
performed. The application has been created on MATLAB environment with operating system as windows
7.
Nature grasping by a cable-driven under-actuated anthropomorphic robotic handTELKOMNIKA JOURNAL
Human hand is the best sample for humanoid robotic hand and a nature grasping is the final target that most robotic hands are pursuing. Many prior researches had been done in virtual and real for simulation the human grasping. Unfortunately, there is no perfect solution to duplicate the nature grasping of human. The main difficulty comes from three points. 1. How to 3D modelling and fabricate the real hand. 2. How actuated the robotic hand as real hand. 3. How to grasp objects in different shapes like human hand. To deal with these three problems and further to provide a partial solution for duplicate human grasping, this paper introduces our method to solve these problems from robotic hand design, fabrication, actuation and grasping plan. Our modelling progress takes only around 12 minutes that include 10 minutes of 3D scanning of a real human hand and two minutes for changing the scanned model to an articulated model by running our algorithm. Our grasping plan is based on the sampled trajectory and easy to implement for grasping different objects. Followed these steps, a seven DOF robotic hand is created and tested in the experiments.
This paper introduces a new concept for the establishment of human-robot symbiotic relationship. The
system is based on the implementation of knowledge-based image processing methodologies for model
based vision and intelligent task scheduling for an autonomous social robot. This paper aims to develop an
automatic translation of static gestures of alphabets and signs in American Sign Language (ASL), using
neural network with backpropagation algorithm. System deals with images of bare hands to achieve the
recognition task. For each individual sign 10 sample images have been considered, which means in
total300 samples have been processed. In order to compare between the training set of signs and the
considered sample images, are converted into feature vectors. Experimental results reveal that this can
recognize selected ASL signs (accuracy of 92.00%). Finally, the system has been implemented issuing hand
gesture commands for ASL to a robot car, named “Moto-robo”.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Hand gesture classification is popularly used in
wide applications like Human-Machine Interface, Virtual
Reality, Sign Language Recognition, Animations etc. The
classification accuracy of static gestures depends on the
technique used to extract the features as well as the classifier
used in the system. To achieve the invariance to illumination
against complex background, experimentation has been
carried out to generate a feature vector based on skin color
detection by fusing the Fourier descriptors of the image with
its geometrical features. Such feature vectors are then used in
Neural Network environment implementing Back
Propagation algorithm to classify the hand gestures. The set
of images for the hand gestures used in the proposed research
work are collected from the standard databases viz.
Sebastien Marcel Database, Cambridge Hand Gesture Data
set and NUS Hand Posture dataset. An average classification
accuracy of 95.25% has been observed which is on par with
that reported in the literature by the earlier researchers.
Gesture Recognition Review: A Survey of Various Gesture Recognition AlgorithmsIJRES Journal
This paper presents simple as well as effective methods to realize hand gesture recognition. Gesture recognition is mainly apprehensive on analysing the functionality of human Intelligence. The main aim of gesture detection and recognition is to design an efficient system which is able to recognize particular human gestures and use these detected gestures to transfer information or for controlling devices. Hand gestures enable a vivid complementary modal to communicate with speech for expressing ones thought of idea. The information which is associated with hand gestures detection in a conversation is extent or degree, detection discourse structure, spatial and temporal design structure. Based on the above given points the paper discusses various models of gesture detection and recognition.
This paper presents the maneuver of mouse pointer and performs various mouse operations such as left
click, right click, double click, drag etc using gestures recognition technique. Recognizing gestures is a
complex task which involves many aspects such as motion modeling, motion analysis, pattern recognition
and machine learning.
Keeping all the essential factors in mind a system has been created which recognizes the movement of
fingers and various patterns formed by them. Color caps have been used for fingers to distinguish it from
the background color such as skin color. Thus recognizing the gestures various mouse events have been
performed. The application has been created on MATLAB environment with operating system as windows
7.
Nature grasping by a cable-driven under-actuated anthropomorphic robotic handTELKOMNIKA JOURNAL
Human hand is the best sample for humanoid robotic hand and a nature grasping is the final target that most robotic hands are pursuing. Many prior researches had been done in virtual and real for simulation the human grasping. Unfortunately, there is no perfect solution to duplicate the nature grasping of human. The main difficulty comes from three points. 1. How to 3D modelling and fabricate the real hand. 2. How actuated the robotic hand as real hand. 3. How to grasp objects in different shapes like human hand. To deal with these three problems and further to provide a partial solution for duplicate human grasping, this paper introduces our method to solve these problems from robotic hand design, fabrication, actuation and grasping plan. Our modelling progress takes only around 12 minutes that include 10 minutes of 3D scanning of a real human hand and two minutes for changing the scanned model to an articulated model by running our algorithm. Our grasping plan is based on the sampled trajectory and easy to implement for grasping different objects. Followed these steps, a seven DOF robotic hand is created and tested in the experiments.
This paper introduces a new concept for the establishment of human-robot symbiotic relationship. The
system is based on the implementation of knowledge-based image processing methodologies for model
based vision and intelligent task scheduling for an autonomous social robot. This paper aims to develop an
automatic translation of static gestures of alphabets and signs in American Sign Language (ASL), using
neural network with backpropagation algorithm. System deals with images of bare hands to achieve the
recognition task. For each individual sign 10 sample images have been considered, which means in
total300 samples have been processed. In order to compare between the training set of signs and the
considered sample images, are converted into feature vectors. Experimental results reveal that this can
recognize selected ASL signs (accuracy of 92.00%). Finally, the system has been implemented issuing hand
gesture commands for ASL to a robot car, named “Moto-robo”.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Hand Shape Based Gesture Recognition in Hardwareijsrd.com
It is possible to recognize and classify ten hand gestures based solely on their shapes. This paper discusses a simple recognition algorithm that uses three shape-based features of a hand to identify what gesture it is conveying. The overall algorithm has three main steps: segmentation, feature calculation, and classification. The algorithm takes an input image of a hand gesture and calculates three features of the image, two based on compactness, and one based on radial distance. The parameters found in the classification step were obtained empirically using 200 hand images. The algorithm was tested on another 200 hand images, and was able to
Vision based human computer interface using colour detectioneSAT Journals
Abstract In this paper we have tried to present an approach to Human Computer Interaction (HCI). Here we have tried to control actions
associated with mouse. Each mouse actions are associated to a colour pointer. These colour pointer are acquired as input using
web camera. The acquired colour pointer are processed using colour detection technique.
Keywords: Human Computer Interaction, Web Camera, Colour Detection, Colour Subtraction.
Matching Sketches with Digital Face Images using MCWLD and Image Moment Invar...iosrjce
Face recognition is an important problem in many application domains. Matching sketches with
digital face image is important in solving crimes and capturing criminals. It is a computer application for
automatically identifying a person from a still image. Law enforcement agencies are progressively using
composite sketches and forensic sketches for catching the criminals. This paper presents two algorithms that
efficiently retrieve the matched results. First method uses multiscale circular Weber’s local descriptor to encode
more discriminative local micro patterns from local regions. Second method uses image moments, it extracts
discriminative shape, orientation, and texture features from local regions of a face. The discriminating
information from both sketch and digital image is compared using appropriate distance measure. The
contributions of this research paper are: i) Comparison of multiscale circular Weber’s local descriptor with
image moment for matching sketch to digital image, ii) Analysis of these algorithms on viewed face sketch,
forensic face sketch and composite face sketch databases
Hand gesture recognition using support vector machinetheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Enhancing Security and Privacy Issue in Airport by Biometric based Iris Recog...idescitation
Few years ago a self service has been predominant way of passenger at airport.
For the passenger that is a very enjoyable and comfort situation because it keeps control
over all process during their complete journey. For airport and for airlines is also very
interesting evolution because self service allows increasing capacity of airport without any
significant extra investment. However success of self service induces one potential risk. That
is of lack of human contact between airline operator and passenger, there is a problem in
identifying a passenger. This is definitely the problem for immigrations forcibly. This
potential risk of the industry is needed to be addressed and biometrics definitely can solve
this kind of problem. Nowadays biometric is considered to be the most important and
reliable method for personal identification. Iris recognition is considered as most personal
identification.
Stereo Correspondence Algorithms for Robotic Applications Under Ideal And Non...CSCJournals
The use of visual information in real time applications such as in robotic pick, navigation, obstacle avoidance etc. has been widely used in many sectors for enabling them to interact with its environment. Robotics require computationally simpler and easy to implement stereo vision algorithms that will provide reliable and accurate results under real time constraint. Stereo vision is a less expensive, passive sensing technique, for inferring the three dimensional position of objects from two or more simultaneous views of a scene and there is no interference with other sensing devices if multiple robots are present in the same environment. Stereo correspondence aims at finding matching points in the stereo image pair based on Lambertian criteria to obtain disparity. The correspondence algorithm will provide high resolution disparity maps of the scene by comparing two views of the scene under the study. By using the principle of triangulation and with the help of camera parameters, depth information can be extracted from this disparity .Since the focus is on real-time application, only the local stereo correspondence algorithms are considered. A comparative study based on error and computational costs are done between two area based algorithms. Evaluation of Sum of absolute Difference algorithm, which is less computationally expensive, suitable for ideal lightening condition and a more accurate adaptive binary support window algorithm that can handle of non-ideal lighting conditions are taken for this study. To simplify the correspondence search, rectified stereo image pairs are used as inputs.
Hand Gesture Recognition Using Statistical and Artificial Geometric Methods :...caijjournal
Gesture recognition represents the silent language that can be done with robots as well as they done to us,
this overseas language ensures that everyone can understand the meaning of the gesturing as well as can
reply and interact with. Because of that this silent language has chosen for deaf people in which can make
their communication easier between each of them as well as with other people.
In this paper we have brought to the table two different outstanding gesture recognition systems, those two
techniques achieved high ratio of recognition percentage as well as that are invariant-free techniques,
especially rotation perturbation that hinders the achievement of high level recognition percentage, the first
method is the recognition of hand gesture with the help of dynamic circle template and second one using
variable length chromosome generic algorithm, these two methods has been applied to different people and
the main objective was to reduce the database size used for training.
A Study of An Optical Mouse to Customize Ii for Implementation of Wireless Dr...rahulmonikasharma
The paper representsthe study of wireless mouse and implementation of wireless draw pen using Bluetooth Logitech mouse and complete understanding of mouse work and then customizing the same mouse to work as a draw pen in paint application using a simple hand finger. As drawing image by hand in digital format is difficult in any drawing application so to overcome this drawback draw pen is proposed.
A Shot Boundary Detection Method for News Video Based Human Skin Region (Face...ijsrd.com
A New simple approach to detect, classify shot boundaries and store shot boundary frames in Video sequence using human skin region detection based approach is proposed. Human skin region detection is the process of detecting skin region in sequence of frames. Skin region detection is mainly used for the identification of the human face detection. This approach is very much suitable for finding shots in TV News so that we can classify anchor and non-anchor frames to save the overall time which is required to watch overall news.
Hand and wrist localization approach: sign language recognition Sana Fakhfakh
This paper proposes a new hand detection and wrist localization method which presents an important step in the hand gesture recognizing process. The wrist localization step has not been given much attention and the existing works are limited and include many conditions. Our proposed approach was evaluated on a public dataset whose obtained results underscore its performance. We highlight through a comparative study with existing work, the superiority of our approach and the importance of the wrist localization step. We also propose to benefit from our proposed method which can be applied in the sign language recognition domain, and more precisely in the Arabic digit sign language recognition.
A Deep Neural Framework for Continuous Sign Language Recognition by Iterative...ijtsrd
Sign Language SL is a medium of communication for physically disabled people. It is a gesture based language for communication of dumb and deaf people. These people communicate by using different actions of hands, where each different action means something. Sign language is the only way of conversation for deaf and dumb people. It is very difficult to understand this language for the common people. Hence sign language recognition has become an important task. There is a necessity for a translator to communicate with the world. Real time translator for sign language provides a medium to communicate with others. Previous methods employs sensor gloves, hat mounted cameras, armband etc. which has wearing difficulties and have noisy behaviour. To alleviate this problem, a real time gesture recognition system using Deep Learning DL is proposed. It enables to achieve improvements on the gesture recognition performance. Jeni Moni | Anju J Prakash ""A Deep Neural Framework for Continuous Sign Language Recognition by Iterative Training: Survey"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30032.pdf
Paper Url : https://www.ijtsrd.com/engineering/computer-engineering/30032/a-deep-neural-framework-for-continuous-sign-language-recognition-by-iterative-training-survey/jeni-moni
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin detection is one of the most important steps in this way. Though there are some methods to detect human skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can have color similar to skin. In this paper, we have proposed three methods that can identify an anime character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are primarily designed for human skin detection. Our methods are based on RGB values and their comparative relations.
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and
pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin
detection is one of the most important steps in this way. Though there are some methods to detect human
skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from
human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among
themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can
have color similar to skin. In this paper, we have proposed three methods that can identify an anime
character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are
primarily designed for human skin detection. Our methods are based on RGB values and their comparative
relations.
Visual hull construction from semitransparent coloured silhouettesijcga
This paper attempts to create coloured
semi
-
transparent shadow images that can be projected onto
multiple screens simultaneously from different viewpoints. The inputs to this approach are a set of coloured
shadow images and view angles, projection information and light configurations for the f
inal projections.
We propose a method to convert coloured semi
-
transparent shadow images to a 3D visual hull
. A
shadowpix type method is used to incorporate varying ratio RGB values for each voxel. This computes the
desired image independently for each vie
wpoint from an arbitrary angle. An attenuation factor is used to
curb the coloured shadow images beyond a certain distance. The end result is a continuous animated
image that changes due to the rotated projection of the transparent visual hull.
A PREDICTION METHOD OF GESTURE TRAJECTORY BASED ON LEAST SQUARES FITTING MODELVLSICS Design
Implicit interaction based on context information is widely used and studied in the virtual scene. In context
based human computer interaction, the meaning of action A is well defined. For instance, the right wave is
defined turning paper or PPT in context B, And it mean volume up in context C. However, we cannot use
the context information when we select the object to be manipulated. In view of this situation, this paper
proposes using the least squares fitting curve beam to predict the user's trajectory, so as to determine what
object the user’s wants to operate. At the same time, the fitting effects of the three curves were compared,
and the curve which is more accord with the hand movement trajectory is obtained. In addition, using the
bounding box size control the Z variable to move in an appropriate location. Experimental results show
that the proposed in this paper based on bounding box size to control the Z variables get a good effect; by
fitting the trajectory of a human hand, to predict the object that the subjects would like to operate. The
correct rate is 91%.
A PREDICTION METHOD OF GESTURE TRAJECTORY BASED ON LEAST SQUARES FITTING MODELVLSICS Design
Implicit interaction based on context information is widely used and studied in the virtual scene. In context
based human computer interaction, the meaning of action A is well defined. For instance, the right wave is
defined turning paper or PPT in context B, And it mean volume up in context C. However, we cannot use
the context information when we select the object to be manipulated. In view of this situation, this paper
proposes using the least squares fitting curve beam to predict the user's trajectory, so as to determine what
object the user’s wants to operate. At the same time, the fitting effects of the three curves were compared,
and the curve which is more accord with the hand movement trajectory is obtained. In addition, using the
bounding box size control the Z variable to move in an appropriate location. Experimental results show
that the proposed in this paper based on bounding box size to control the Z variables get a good effect; by
fitting the trajectory of a human hand, to predict the object that the subjects would like to operate. The
correct rate is 91%.
Hand Shape Based Gesture Recognition in Hardwareijsrd.com
It is possible to recognize and classify ten hand gestures based solely on their shapes. This paper discusses a simple recognition algorithm that uses three shape-based features of a hand to identify what gesture it is conveying. The overall algorithm has three main steps: segmentation, feature calculation, and classification. The algorithm takes an input image of a hand gesture and calculates three features of the image, two based on compactness, and one based on radial distance. The parameters found in the classification step were obtained empirically using 200 hand images. The algorithm was tested on another 200 hand images, and was able to
Vision based human computer interface using colour detectioneSAT Journals
Abstract In this paper we have tried to present an approach to Human Computer Interaction (HCI). Here we have tried to control actions
associated with mouse. Each mouse actions are associated to a colour pointer. These colour pointer are acquired as input using
web camera. The acquired colour pointer are processed using colour detection technique.
Keywords: Human Computer Interaction, Web Camera, Colour Detection, Colour Subtraction.
Matching Sketches with Digital Face Images using MCWLD and Image Moment Invar...iosrjce
Face recognition is an important problem in many application domains. Matching sketches with
digital face image is important in solving crimes and capturing criminals. It is a computer application for
automatically identifying a person from a still image. Law enforcement agencies are progressively using
composite sketches and forensic sketches for catching the criminals. This paper presents two algorithms that
efficiently retrieve the matched results. First method uses multiscale circular Weber’s local descriptor to encode
more discriminative local micro patterns from local regions. Second method uses image moments, it extracts
discriminative shape, orientation, and texture features from local regions of a face. The discriminating
information from both sketch and digital image is compared using appropriate distance measure. The
contributions of this research paper are: i) Comparison of multiscale circular Weber’s local descriptor with
image moment for matching sketch to digital image, ii) Analysis of these algorithms on viewed face sketch,
forensic face sketch and composite face sketch databases
Hand gesture recognition using support vector machinetheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Enhancing Security and Privacy Issue in Airport by Biometric based Iris Recog...idescitation
Few years ago a self service has been predominant way of passenger at airport.
For the passenger that is a very enjoyable and comfort situation because it keeps control
over all process during their complete journey. For airport and for airlines is also very
interesting evolution because self service allows increasing capacity of airport without any
significant extra investment. However success of self service induces one potential risk. That
is of lack of human contact between airline operator and passenger, there is a problem in
identifying a passenger. This is definitely the problem for immigrations forcibly. This
potential risk of the industry is needed to be addressed and biometrics definitely can solve
this kind of problem. Nowadays biometric is considered to be the most important and
reliable method for personal identification. Iris recognition is considered as most personal
identification.
Stereo Correspondence Algorithms for Robotic Applications Under Ideal And Non...CSCJournals
The use of visual information in real time applications such as in robotic pick, navigation, obstacle avoidance etc. has been widely used in many sectors for enabling them to interact with its environment. Robotics require computationally simpler and easy to implement stereo vision algorithms that will provide reliable and accurate results under real time constraint. Stereo vision is a less expensive, passive sensing technique, for inferring the three dimensional position of objects from two or more simultaneous views of a scene and there is no interference with other sensing devices if multiple robots are present in the same environment. Stereo correspondence aims at finding matching points in the stereo image pair based on Lambertian criteria to obtain disparity. The correspondence algorithm will provide high resolution disparity maps of the scene by comparing two views of the scene under the study. By using the principle of triangulation and with the help of camera parameters, depth information can be extracted from this disparity .Since the focus is on real-time application, only the local stereo correspondence algorithms are considered. A comparative study based on error and computational costs are done between two area based algorithms. Evaluation of Sum of absolute Difference algorithm, which is less computationally expensive, suitable for ideal lightening condition and a more accurate adaptive binary support window algorithm that can handle of non-ideal lighting conditions are taken for this study. To simplify the correspondence search, rectified stereo image pairs are used as inputs.
Hand Gesture Recognition Using Statistical and Artificial Geometric Methods :...caijjournal
Gesture recognition represents the silent language that can be done with robots as well as they done to us,
this overseas language ensures that everyone can understand the meaning of the gesturing as well as can
reply and interact with. Because of that this silent language has chosen for deaf people in which can make
their communication easier between each of them as well as with other people.
In this paper we have brought to the table two different outstanding gesture recognition systems, those two
techniques achieved high ratio of recognition percentage as well as that are invariant-free techniques,
especially rotation perturbation that hinders the achievement of high level recognition percentage, the first
method is the recognition of hand gesture with the help of dynamic circle template and second one using
variable length chromosome generic algorithm, these two methods has been applied to different people and
the main objective was to reduce the database size used for training.
A Study of An Optical Mouse to Customize Ii for Implementation of Wireless Dr...rahulmonikasharma
The paper representsthe study of wireless mouse and implementation of wireless draw pen using Bluetooth Logitech mouse and complete understanding of mouse work and then customizing the same mouse to work as a draw pen in paint application using a simple hand finger. As drawing image by hand in digital format is difficult in any drawing application so to overcome this drawback draw pen is proposed.
A Shot Boundary Detection Method for News Video Based Human Skin Region (Face...ijsrd.com
A New simple approach to detect, classify shot boundaries and store shot boundary frames in Video sequence using human skin region detection based approach is proposed. Human skin region detection is the process of detecting skin region in sequence of frames. Skin region detection is mainly used for the identification of the human face detection. This approach is very much suitable for finding shots in TV News so that we can classify anchor and non-anchor frames to save the overall time which is required to watch overall news.
Hand and wrist localization approach: sign language recognition Sana Fakhfakh
This paper proposes a new hand detection and wrist localization method which presents an important step in the hand gesture recognizing process. The wrist localization step has not been given much attention and the existing works are limited and include many conditions. Our proposed approach was evaluated on a public dataset whose obtained results underscore its performance. We highlight through a comparative study with existing work, the superiority of our approach and the importance of the wrist localization step. We also propose to benefit from our proposed method which can be applied in the sign language recognition domain, and more precisely in the Arabic digit sign language recognition.
A Deep Neural Framework for Continuous Sign Language Recognition by Iterative...ijtsrd
Sign Language SL is a medium of communication for physically disabled people. It is a gesture based language for communication of dumb and deaf people. These people communicate by using different actions of hands, where each different action means something. Sign language is the only way of conversation for deaf and dumb people. It is very difficult to understand this language for the common people. Hence sign language recognition has become an important task. There is a necessity for a translator to communicate with the world. Real time translator for sign language provides a medium to communicate with others. Previous methods employs sensor gloves, hat mounted cameras, armband etc. which has wearing difficulties and have noisy behaviour. To alleviate this problem, a real time gesture recognition system using Deep Learning DL is proposed. It enables to achieve improvements on the gesture recognition performance. Jeni Moni | Anju J Prakash ""A Deep Neural Framework for Continuous Sign Language Recognition by Iterative Training: Survey"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30032.pdf
Paper Url : https://www.ijtsrd.com/engineering/computer-engineering/30032/a-deep-neural-framework-for-continuous-sign-language-recognition-by-iterative-training-survey/jeni-moni
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin detection is one of the most important steps in this way. Though there are some methods to detect human skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can have color similar to skin. In this paper, we have proposed three methods that can identify an anime character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are primarily designed for human skin detection. Our methods are based on RGB values and their comparative relations.
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and
pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin
detection is one of the most important steps in this way. Though there are some methods to detect human
skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from
human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among
themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can
have color similar to skin. In this paper, we have proposed three methods that can identify an anime
character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are
primarily designed for human skin detection. Our methods are based on RGB values and their comparative
relations.
Visual hull construction from semitransparent coloured silhouettesijcga
This paper attempts to create coloured
semi
-
transparent shadow images that can be projected onto
multiple screens simultaneously from different viewpoints. The inputs to this approach are a set of coloured
shadow images and view angles, projection information and light configurations for the f
inal projections.
We propose a method to convert coloured semi
-
transparent shadow images to a 3D visual hull
. A
shadowpix type method is used to incorporate varying ratio RGB values for each voxel. This computes the
desired image independently for each vie
wpoint from an arbitrary angle. An attenuation factor is used to
curb the coloured shadow images beyond a certain distance. The end result is a continuous animated
image that changes due to the rotated projection of the transparent visual hull.
A PREDICTION METHOD OF GESTURE TRAJECTORY BASED ON LEAST SQUARES FITTING MODELVLSICS Design
Implicit interaction based on context information is widely used and studied in the virtual scene. In context
based human computer interaction, the meaning of action A is well defined. For instance, the right wave is
defined turning paper or PPT in context B, And it mean volume up in context C. However, we cannot use
the context information when we select the object to be manipulated. In view of this situation, this paper
proposes using the least squares fitting curve beam to predict the user's trajectory, so as to determine what
object the user’s wants to operate. At the same time, the fitting effects of the three curves were compared,
and the curve which is more accord with the hand movement trajectory is obtained. In addition, using the
bounding box size control the Z variable to move in an appropriate location. Experimental results show
that the proposed in this paper based on bounding box size to control the Z variables get a good effect; by
fitting the trajectory of a human hand, to predict the object that the subjects would like to operate. The
correct rate is 91%.
A PREDICTION METHOD OF GESTURE TRAJECTORY BASED ON LEAST SQUARES FITTING MODELVLSICS Design
Implicit interaction based on context information is widely used and studied in the virtual scene. In context
based human computer interaction, the meaning of action A is well defined. For instance, the right wave is
defined turning paper or PPT in context B, And it mean volume up in context C. However, we cannot use
the context information when we select the object to be manipulated. In view of this situation, this paper
proposes using the least squares fitting curve beam to predict the user's trajectory, so as to determine what
object the user’s wants to operate. At the same time, the fitting effects of the three curves were compared,
and the curve which is more accord with the hand movement trajectory is obtained. In addition, using the
bounding box size control the Z variable to move in an appropriate location. Experimental results show
that the proposed in this paper based on bounding box size to control the Z variables get a good effect; by
fitting the trajectory of a human hand, to predict the object that the subjects would like to operate. The
correct rate is 91%.
A PREDICTION METHOD OF GESTURE TRAJECTORY BASED ON LEAST SQUARES FITTING MODELVLSICS Design
Implicit interaction based on context information is widely used and studied in the virtual scene. In context
based human computer interaction, the meaning of action A is well defined. For instance, the right wave is
defined turning paper or PPT in context B, And it mean volume up in context C. However, we cannot use
the context information when we select the object to be manipulated. In view of this situation, this paper
proposes using the least squares fitting curve beam to predict the user's trajectory, so as to determine what
object the user’s wants to operate. At the same time, the fitting effects of the three curves were compared,
and the curve which is more accord with the hand movement trajectory is obtained. In addition, using the
bounding box size control the Z variable to move in an appropriate location. Experimental results show
that the proposed in this paper based on bounding box size to control the Z variables get a good effect; by
fitting the trajectory of a human hand, to predict the object that the subjects would like to operate. The
correct rate is 91%.
Hand Segmentation Techniques to Hand Gesture Recognition for Natural Human Co...Waqas Tariq
This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm where three algorithms for hand segmentation using different color spaces with required morphological processing have were utilized. Hand tracking and segmentation algorithm (HTS) is found to be most efficient to handle the challenges of vision based system such as skin color detection, complex background removal and variable lighting condition. Noise may contain, sometime, in the segmented image due to dynamic background. An edge traversal algorithm was developed and applied on the segmented hand contour for removal of unwanted background noise.
Mouse Simulation Using Two Coloured Tapesijistjournal
In this paper, we present a novel approach for Human Computer Interaction (HCI) where, we control cursor movement using a real-time camera. Current methods involve changing mouse parts such as adding more buttons or changing the position of the tracking ball. Instead, our method is to use a camera and computer vision technology, such as image segmentation and gesture recognition, to control mouse tasks (left and right clicking, double-clicking, and scrolling) and we show how it can perform everything as current mouse devices can.
The software will be developed in JAVA language. Recognition and pose estimation in this system are user independent and robust as we will be using colour tapes on our finger to perform actions. The software can be used as an intuitive input interface to applications that require multi-dimensional control e.g. computer games etc.
Mouse Simulation Using Two Coloured Tapes ijistjournal
In this paper, we present a novel approach for Human Computer Interaction (HCI) where, we control cursor movement using a real-time camera. Current methods involve changing mouse parts such as adding more buttons or changing the position of the tracking ball. Instead, our method is to use a camera and computer vision technology, such as image segmentation and gesture recognition, to control mouse tasks (left and right clicking, double-clicking, and scrolling) and we show how it can perform everything as current mouse devices can.
The software will be developed in JAVA language. Recognition and pose estimation in this system are user independent and robust as we will be using colour tapes on our finger to perform actions. The software can be used as an intuitive input interface to applications that require multi-dimensional control e.g. computer games etc.
3D Human Hand Posture Reconstruction Using a Single 2D ImageWaqas Tariq
Passive sensing of the 3D geometric posture of the human hand has been studied extensively over the past decade. However, these research efforts have been hampered by the computational complexity caused by inverse kinematics and 3D reconstruction. In this paper, our objective focuses on 3D hand posture estimation based on a single 2D image with aim of robotic applications. We introduce the human hand model with 27 degrees of freedom (DOFs) and analyze some of its constraints to reduce the DOFs without any significant degradation of performance. A novel algorithm to estimate the 3D hand posture from eight 2D projected feature points is proposed. Experimental results using real images confirm that our algorithm gives good estimates of the 3D hand pose. Keywords: 3D hand posture estimation; Model-based approach; Gesture recognition; human- computer interface; machine vision.
We propose an image-based method using Contourlet transform [5] to detect liveness in fingerprint biometric systems. We observe that real and spoof fingerprint images exhibit
different textural characteristics. Wavelet transform although widely used for liveness detection is not the ideal one. Wavelets are not very effective in representing images containing lines and contours [5]. Recent Contourlet transform allows representing contours in a more efficient way than the wavelets [5]. Fingerprint is made of only contours of ridges; hence Contourlet transform is more suitable for fingerprint processing than the wavelets. Therefore, we use Contourlet energy and co-occurrence signatures to capture textural intricacies of images. After downsizing features with Plus l – take away r method, we test them on various classifiers: logistic regression, support vector machine and AdTree using our databases consisting of 185real, 90 Fun-Doh (Play-Doh) and 150 Gummy fingerprint images. We then select the best classifier and use at as a base classifier to form an ensemble classifier obtained by fusing a
stack of “K” base classifiers using the “Majority Voting Rule” (i.e. bagging). Experimentalresults indicate that, the new liveness detection approach is very promising as it needs only one
fingerprint and no extra hardware to detect vitality
We propose an image-based method using Contourlet transform [5] to detect liveness in
fingerprint biometric systems. We observe that real and spoof fingerprint images exhibit
different textural characteristics. Wavelet transform although widely used for liveness detection
is not the ideal one. Wavelets are not very effective in representing images containing lines and
contours [5]. Recent Contourlet transform allows representing contours in a more efficient way
than the wavelets [5]. Fingerprint is made of only contours of ridges; hence Contourlet
transform is more suitable for fingerprint processing than the wavelets. Therefore, we use
Contourlet energy and co-occurrence signatures to capture textural intricacies of images. After
downsizing features with Plus l – take away r method, we test them on various classifiers:
logistic regression, support vector machine and AdTree using our databases consisting of 185
real, 90 Fun-Doh (Play-Doh) and 150 Gummy fingerprint images. We then select the best
classifier and use at as a base classifier to form an ensemble classifier obtained by fusing a
stack of “K” base classifiers using the “Majority Voting Rule” (i.e. bagging). Experimental
results indicate that, the new liveness detection approach is very promising as it needs only one
fingerprint and no extra hardware to detect vitality
HUMAN COMPUTER INTERACTION ALGORITHM BASED ON SCENE SITUATION AWARENESScsandit
Implicit interaction based on context information is widely used and studied in the virtual scene.In context based human computer interaction, the meaning of action A is well defined. For instance, the right wave is defined turning paper or PPT in context B, And it mean volume up in context C. However, Select object in a virtual scene with multiple objects, context information is not fit. In view of this situation, this paper proposes using the least squares fitting curve beam to
predict the user's trajectory, so as to determine what object the user’s wants to operate .And fitting the starting position of the straight line according to the change of the discrete table. And
using the bounding box size control the Z variable to move in an appropriate location. Experimental results show that the proposed in this paper based on bounding box size to control
the Z variables get a good effect; by fitting the trajectory of a human hand, to predict the object that the subjects would like to operate. The correct rate is 88.6%.
Human Computer Interaction Algorithm Based on Scene Situation Awareness cscpconf
Implicit interaction based on context information is widely used and studied in the virtual scene.
In context based human computer interaction, the meaning of action A is well defined. For
instance, the right wave is defined turning paper or PPT in context B, And it mean volume up in
context C. However, Select object in a virtual scene with multiple objects, context information is
not fit. In view of this situation, this paper proposes using the least squares fitting curve beam to
predict the user's trajectory, so as to determine what object the user’s wants to operate .And
fitting the starting position of the straight line according to the change of the discrete table. And
using the bounding box size control the Z variable to move in an appropriate location.
Experimental results show that the proposed in this paper based on bounding box size to control
the Z variables get a good effect; by fitting the trajectory of a human hand, to predict the object
that the subjects would like to operate. The correct rate is 88.6%.
A revolution in computer interface design is changing the way we think about computers. Rather than typing on a keyboard and watching a television monitor, Augmented Reality lets people use familiar, everyday objects in ordinary ways. A revolution in computer interface design is changing the way we think about computers. Rather than typing on a keyboard and watching a television monitor, Augmented Reality lets people use familiar, everyday objects in ordinary ways. This paper surveys the field of Augmented Reality, in which 3-D virtual objects are integrated into a 3-D real environment in real time. It describes the medical, manufacturing, visualization, path planning, entertainment and military applications that have been explored. This paper describes the characteristics of Augmented Reality systems. Registration and sensing errors are two of the biggest problems in building effective Augmented Reality systems, so this paper throws light on problems. Future directions and areas requiring further research are discussed. This survey provides a starting point for anyone interested in researching or using Augmented Reality.
Similar to Using Watershed Transform for Vision-based Two-Hand Occlusion in an Interactive AR Environment (20)
Securing Cloud Computing Through IT GovernanceITIIIndustries
Lack of alignment between information technology (IT) and the business is a problem facing many organizations. Most organizations, today, fundamentally depend on IT. When IT and the business are aligned in an organization, IT delivers what the business needs and the business is able to deliver what the market needs. IT has become a strategic function for most organizations, and it is imperative that IT and business are aligned. IT governance is one of the most powerful ways to achieve IT to business alignment. Furthermore, as the use of cloud computing for delivering IT functions becomes pervasive, organizations using cloud computing must effectively apply IT governance to it. While cloud computing presents tremendous
opportunities, it comes with risks as well. Information security
is one of the top risks in cloud computing. Thus, IT governance must be applied to cloud computing information security to help manage the risks associated with cloud computing information security. This study advances knowledge by extending IT governance to cloud computing and information security governance.
Information Technology in Industry(ITII) - November Issue 2018ITIIIndustries
IT Industry publishes original research articles, review articles, and extended versions of conference papers. Articles resulting from research of both theoretical and/or practical natures performed by academics and/or industry practitioners are welcome. IT in Industry aims to become a leading IT journal with a high impact factor.
Design of an IT Capstone Subject - Cloud RoboticsITIIIndustries
This paper describes the curriculum of the three year IT undergraduate program at La Trobe University, and the faculty requirements in designing a capstone subject, followed by the ACM’s recommended IT curriculum covering the five pillars of the IT discipline. Cloud robotics, a broad multidisciplinary research area, requiring expertise in all five pillars with mechatronics, is an ideal candidate to offer capstone experiences to IT students. Therefore, in this paper, we propose a long term
master project in developing a cloud robotics testbed, with many capstone sub-projects spanning across the five IT pillars, to meet the objectives of capstone experience. This paper also describes the design and implementation of the testbed, and proposes potential capstone projects for students with different interests.
Dimensionality Reduction and Feature Selection Methods for Script Identificat...ITIIIndustries
The goal of this research is to explore effects of dimensionality reduction and feature selection on the problem of script identification from images of printed documents. The kadjacent segment is ideal for this use due to its ability to capture visual patterns. We have used principle component analysis to reduce the size of our feature matrix to a handier size that can be trained easily, and experimented by including varying combinations of dimensions of the super feature set. A modular
approach in neural network was used to classify 7 languages – Arabic, Chinese, English, Japanese, Tamil, Thai and Korean.
Image Matting via LLE/iLLE Manifold LearningITIIIndustries
Accurately extracting foreground objects is the problem of isolating the foreground in images and video, called image matting which has wide applications in digital photography. This problem is severely ill-posed in the sense that, at each pixel, one must estimate the foreground and background pixels and the so-called alpha value from only pixel information. The most recent work in natural image matting rely on local smoothness assumptions about foreground and background colours on which a cost function has been established. In this paper, we propose an extension to the class of affinity based matting techniques by incorporating local manifold structural
information to produce both a smoother matte based on the socalled improved Locally Linear Embedding. We illustrate our new algorithm using the standard benchmark images and very comparable results have been obtained.
Annotating Retina Fundus Images for Teaching and Learning Diabetic Retinopath...ITIIIndustries
With the improvement in IT industry, more and more application of computer software is introduced in teaching and learning. In this paper, we discuss the development process of such software. Diabetic Retinopathy is a common complication for diabetic patients. It may cause sight loss if not treated early. There are several stages of this disease. Fundus imagery is required to identify the stage and severity of the disease. Due to the lack of proper dataset of the fundus images and proper annotation, it is very difficult to perform research on this topic. Moreover, medical students are often facing difficulty with identifying the diseases in later stage of their practice as they may not have seen a sample of all of the stages of Diabetic Retinopathy problems. To mitigate the problem, we have collected fundus images from different geographic area of Bangladesh and designed an annotation software to store information about the patient, the infection level and their locations in the images. Sometimes, it is difficult to select all appropriate pixels of the infected region. To resolve the issue, we have introduced a K nearest neighbor (KNN) based technique to accurately select the region of interest (ROI). Once an expert (ophthalmologist) has annotated the images, the software can be used by the students for learning.
A Framework for Traffic Planning and Forecasting using Micro-Simulation Calib...ITIIIndustries
This paper presents the application of microsimulation for traffic planning and forecasting, and proposes a new framework to model complex traffic conditions by calibrating and adjusting traffic parameters of a microsimulation model. By using an open source micro-simulator package, TRANSIMS, in this study, animated and numerical results were produced and analysed. The framework of traffic model calibration was evaluated for its usefulness and practicality. Finally, we discuss future applications such as providing end users with real time traffic information through Intelligent Transport System (ITS) integration.
Investigating Tertiary Students’ Perceptions on Internet SecurityITIIIndustries
Internet security threats have grown from just simple viruses to various forms of computer hacking, scams, impersonation, cyber bullying, and spyware. The Internet has great influence on most people. It has profound influence and one can spend endless hours on internet activities. In particular, youth engage in more online activities than any other age group. Excessive internet usage is an emerging threat that has negative impacts on these youth; hence it is vital to investigate youths' online behavior. This work studies tertiary students’ risk awareness, and provides some findings that allow us to understand their knowledge on risks and their behavior towards online activities. It reveals several important online issues amongst tertiary students; Firstly, the lack of online security awareness; second, a lack of awareness and information about the dangers of rootkits, internet cookies and spyware; thirdly, female students are more unflinching than male students when commenting on social networking sites; fourthly, students are cautious only when obvious security warnings are present; and finally, their usage of internet hotspots is common without fully understanding its associated danger. These findings enable us to recommend types of internet security habits and safety practices that students should adopt in future when they are exposed to online activities. A more holistic approach was considered which aims to minimize any future risks and dangers with online activities involving students.
Blind Image Watermarking Based on Chaotic MapsITIIIndustries
Security of a watermark refers to its resistance to unauthorized detecting and decoding, while watermark robustness refers to the watermark’s resistance against common processing. Many watermarking schemes emphasize robustness more than security. However, a robust watermark is not enough to accomplish protection because the range of hostile attacks is not limited to common processing and distortions. In this paper, we give consideration to watermark security. To achieve this, we employ chaotic maps due to their extreme sensitivity to the initial values. If one fails to provide these values, the watermark will be wrongly extracted. While the chaotic maps provide perfect watermarking security, the proposed scheme is also intended to achieve robustness.
Programmatic detection of spatial behaviour in an agent-based modelITIIIndustries
The automated detection of aspects of spatial behaviour in an agent-based model is necessary for model testing and analysis. In this paper we compare four predictors of herding behaviour in a model of a grazing herbivore. We find that a) the mean number of neighbours adjusted to account for population variation and b) the mean Hamming distance between rows of the two-dimensional environment can be used to detect herding. Visual inspection of the model behaviour revealed that herding occurs when the herbivore mobility reaches a threshold level. Using this threshold we identify a limits for these predictors to use in the program code. These results apply only to one set of parameters and environment size; future research will involve a wider parameter space.
Design of an IT Capstone Subject - Cloud RoboticsITIIIndustries
This paper describes the curriculum of the three year IT undergraduate program at La Trobe University, and the faculty requirements in designing a capstone subject, followed by the ACM’s recommended IT curriculum covering the five pillars of the IT discipline. Cloud robotics, a broad multidisciplinary research area, requiring expertise in all five pillars with mechatronics, is an ideal candidate to offer capstone experiences to IT students. Therefore, in this paper, we propose a long term master project in developing a cloud robotics testbed, with many capstone sub-projects spanning across the five IT pillars, to meet the objectives of capstone experience. This paper also describes the design and implementation of the testbed, and proposes potential capstone projects for students with different interests.
A Smart Fuzzing Approach for Integer Overflow DetectionITIIIndustries
Fuzzing is one of the most commonly used methods to detect software vulnerabilities, a major cause of information security incidents. Although it has advantages of simple design and low error report, its efficiency is usually poor. In this paper we present a smart fuzzing approach for integer overflow detection and a tool, SwordFuzzer, which implements this approach. Unlike standard fuzzing techniques, which randomly change parts of the input file with no information about the underlying syntactic structure of the file, SwordFuzzer uses online dynamic taint analysis to identify which bytes in the input file are used in security sensitive operations and then focuses on mutating such bytes. Thus, the generated inputs are more likely to trigger potential vulnerabilities. We evaluated SwordFuzzer with an example program and a number of real-world applications. The experimental results show that SwordFuzzer can accurately locate the key bytes of the input file and dramatically improve the effectiveness of fuzzing in detecting real-world vulnerabilities
The banking experience for many people today is fundamentally an application of technology to be able to carry out their financial tasks. While the need to visit a bank branch remains essential for a number of activities, increasingly the need to support mobile usage is becoming the central focus of many bank strategies. The core banking systems that process financial transactions must remain highly available and able to support large volumes of activity. These systems represent a long term investment for banks and when the need arises to modernize these large systems, the transformation initiative is often very expensive and of high risk. We present in this paper our experiences in bank modernization and transformation, and outline the strategies for rolling out these large programs. As banking institutions embark upon transformation programs to upgrade their banking channels and core banking systems, it is hoped that the insights presented here are useful as a framework to support these initiatives.
Detecting Fraud Using Transaction Frequency DataITIIIndustries
Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. In this paper, we present a fraud detection method which detects irregular frequency of transaction usage in an Enterprise Resource Planning (ERP) system. We discuss the design, development and empirical evaluation of outlier detection and distance measuring techniques to detect frequency-based anomalies within an individual user’s profile, relative to other similar users. Primarily, we propose three automated techniques: a univariate method, called Boxplot which is based on the sample’s median; and two multivariate methods which use Euclidean distance, for detecting transaction frequency anomalies within each transaction profile. The two multivariate approaches detect potentially fraudulent activities by identifying: (1) users where the Euclidean distance between their transaction-type set is above a certain threshold and (2) users/data points that lie far apart from other users/clusters or represent a small cluster size, using k-means clustering. The proposed methodology allows an auditor to investigate the transaction frequency anomalies and adjust the different parameters, such as the outlier threshold and the Euclidean distance threshold values to tune the number of alerts. The novelty of the proposed technique lies in its ability to automatically trigger alerts from transaction profiles, based on transaction usage performed over a period of time. Experiments were conducted using a real dataset obtained from the production client of a large organization using SAP R/3 (presently the most predominant ERP system), to run its business. The results of this empirical research demonstrate the effectiveness of the proposed approach.
Mapping the Cybernetic Principles of Viable System Model to Enterprise Servic...ITIIIndustries
This paper describes the results of a theoretical mapping of the cybernetic principles of the Viable System Model (VSM) to an Enterprise Service Bus (ESB) model, with the aim to identify the management principles for the integration of services at all levels in the enterprise. This enrichment directly contributes to the viability of service-oriented systems and the justification of Business/IT alignment within enterprise. The model was identified to be suitable for further adaption in the industrial setting planned within Australian governmental departments.
Speech Feature Extraction and Data VisualisationITIIIndustries
—This paper presents a signal processing approach to analyse and identify accent discriminative features of four groups of English as a second language (ESL) speakers, including Chinese, Indian, Japanese, and Korean. The features used for speech recognition include pitch, stress, formant frequencies, the Mel frequency coefficient, log frequency coefficient, and the intensity and duration of vowels spoken. This paper presents our study using the Matlab Speech Analysis Toolbox, and highlights how data processing can be automated and results visualised. The proposed algorithm achieved an average success rate of 57.3% in identifying vowels spoken in a speech by the four nonnative English speaker groups.
Bayesian-Network-Based Algorithm Selection with High Level Representation Fee...ITIIIndustries
A real-world intelligent system consists of three basic modules: environment recognition, prediction (or estimation), and behavior planning. To obtain high quality results in these modules, high speed processing and real time adaptability on a case by case basis are required. In the environment recognition module many different algorithms and algorithm networks exist with varying performance. Thus, a mechanism that selects the best possible algorithm is required. To solve this problem we are using an algorithm selection approach to the problem of natural image understanding. This selection mechanism is based on machine learning; a bottom-up algorithm selection from real-world image features and a top-down algorithm selection using information obtained from a high level symbolic world description and algorithm suitability. The algorithm selection method iterates for each input image until the high-level description cannot be improved anymore. In this paper we present a method of iterative composition of the high level description. This step by step approach allows us to select the best result for each region of the image by evaluating all the intermediary representations and finally keep only the best one.
Instance Selection and Optimization of Neural NetworksITIIIndustries
Credit scoring is an important tool in financial institutions, which can be used in credit granting decision. Credit applications are marked by credit scoring models and those with high marks will be treated as “good”, while those with low marks will be regarded as “bad”. As data mining technique develops, automatic credit scoring systems are warmly welcomed for their high efficiency and objective judgments. Many machine learning algorithms have been applied in training credit scoring models, and ANN is one of them with good performance. This paper presents a higher accuracy credit scoring model based on MLP neural networks trained with back propagation algorithm. Our work focuses on enhancing credit scoring models in three aspects: optimize data distribution in datasets using a new method called Average Random Choosing; compare effects of training-validation-test instances numbers; and find the most suitable number of hidden units. Another contribution of this paper is summarizing the tendency of scoring accuracy of models when the number of hidden units increases. The experiment results show that our methods can achieve high credit scoring accuracy with imbalanced datasets. Thus, credit granting decision can be made by data mining methods using MLP neural networks.
Signature Forgery and the Forger – An Assessment of Influence on Handwritten ...ITIIIndustries
Signatures are widely used as a form of personal authentication. Despite ubiquity in deployment, individual signatures are relatively easy to forge, especially when only the static ‘pictorial’ outcome of the signature is considered at verification time. In this study, we explore opinions on signature usage for verification purposes, and how individuals rate a particular third-party signature in terms of ease of forgeability and their own ability to forge. We examine responses with respect to an individual’s experience of the forgeability/complexity of their own signature. Our study shows that past experience does not generally have an effect on perceived signature complexity nor the perceived effectiveness of an individual to themselves forge a signature. In assessing forgeability, most subjects cite the overall signature complexity and distinguishing features in reaching this decision. Furthermore, our research indicates that individuals typically vary their signature according to the scenario but generally little effort into the production of the signature.
Stability of Individuals in a Fingerprint System across Force LevelsITIIIndustries
This research studied the question: “Are all
individual’s performance stable in a fingerprint recognition
system?” The fingerprints of 154 individuals, provided at
different force levels, were examined using the biometric
menagerie tool, first coined by Doddington et al. in 1998. The
Biometric Menagerie illustrates how each person in a given
dataset performs in a biometric system, by using their genuine
and impostor scores, and providing them a classification based
upon those scores. This research examined the biometric
menagerie classifications across different force levels in a
fingerprint recognition study to uncover if individuals performed
the same over five force levels. The study concluded that they did
not, and a new metric has been created to quantify this
phenomenon. As a result of this discovery, the new metric,
Stability Score Index is described to showcase the movement of
individuals in the menagerie.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.