This document presents research on detecting image forgery using support vector machines. It begins with an abstract discussing how easily images can be digitally manipulated today without leaving traces. It then discusses the most common forgery techniques of splicing, where one image region is cut and pasted into another image, and copy-move, where an image region is copied and pasted within the same image.
The document then reviews previous work on forgery detection techniques. It proposes a new approach that uses preprocessing, feature extraction from image blocks, and support vector machines to classify images as authentic or forged. If forged, principal component analysis is used to identify the forged regions. The approach is tested on splicing and copy-move forgeries and
Implementation of Picwords to Warping Pictures and Keywords through CalligramIRJET Journal
The document describes a system called PicWords that combines images with keywords. It has four main modules: 1) A picture module that takes an input image and generates a silhouette, patches the silhouette into regions, and ranks the patches. 2) A keywords module that collects and ranks keywords. 3) A picture and keywords module that maps keywords to patches. 4) A post-processing module that finalizes the output. The goal is to represent an image and convey additional information about it in a concise visual manner using integrated pictures and words.
IMAGE RECOGNITION USING MATLAB SIMULINK BLOCKSETIJCSEA Journal
The world over, image recognition are essential players in promoting quality object recognition especially in emergency and search-rescue operation. In this paper precise image recognition system using Matlab Simulink Blockset to detect selected object from crowd is presented. The process involves extracting object
features and then recognizes it considering illumination, direction and pose. A Simulink model has been developed to eliminate the tiny elements from the image, then creating segments for precise object recognition. Furthermore, the simulation explores image recognition from the coloured and gray-scale images through image processing techniques in Simulink environment. The tool employed for computation
and simulation is the Matlab image processing blockset. The process comprises morphological operation method which is effective for captured images and video. The results of extensive simulations indicate that this method is suitable for application identifying a person from a crow. The model can be used in emergency and search-rescue operation as well as in medicine, information security, access control, law enforcement, surveillance system, microscopy etc.
The model explains how we can Automate System using Artificial Intelligence.
It broadly concerns about:-
1. Lane Detection.
2. Traffic Sign Classification.
3. Behavioural Cloning.
IRJET - Automatic Licence Plate Detection and RecognitionIRJET Journal
This document describes a system for automatic license plate detection and recognition. The system uses image processing techniques in MATLAB to capture an image of a vehicle license plate, preprocess the image by converting it to grayscale and reducing noise, segment the license plate from the image, and recognize the characters on the plate using optical character recognition. The system is proposed to identify vehicles entering a university campus and check if they are registered in the university's database. The document outlines the methodology, which involves preprocessing, segmentation, character separation, and character recognition steps. It also discusses related work on license plate detection algorithms and presents experimental results demonstrating the system's ability to accurately extract license plate numbers from images.
IRJET- Automatic Traffic Sign Detection and Recognition using CNNIRJET Journal
This document presents a method for automatic traffic sign detection and recognition using convolutional neural networks (CNNs). The proposed system first enhances input images and performs thresholding and region extraction. Features are then extracted and the images are classified using a CNN. The CNN architecture includes convolutional, ReLU, pooling and fully connected layers. The system achieves detection rates over 88% mean average precision and boundary estimation errors under 3 pixels. It runs in real-time at over 7 frames per second on mobile platforms, providing accurate traffic sign detection, recognition and boundary estimation. The method is robust to occlusion, blurring and small targets compared to other methods.
This document discusses color detection using OpenCV in C++. It introduces color detection and OpenCV, with the objective of implementing object-oriented programming concepts to detect pixel colors in a 3-channel RGB image. The architecture involves OpenCV capturing images in BGR format. Implementation calculates spatial moments and central moments of a binary image to determine pixel colors. Future applications include computer vision, object segregation and tracking based on color.
IRJET- Identification of Scene Images using Convolutional Neural Networks - A...IRJET Journal
This document summarizes research on using convolutional neural networks (CNNs) for scene image identification. It first discusses traditional object detection methods and their limitations. CNNs are presented as an improved approach, with convolutional, pooling and fully connected layers to extract features and classify images. Several popular CNN-based object detection algorithms are then summarized, including R-CNN, Fast R-CNN, Faster R-CNN and YOLO. The document concludes that CNN methods provide more accurate object identification compared to traditional algorithms due to their ability to learn from large datasets.
An Image Based PCB Fault Detection and Its Classificationrahulmonikasharma
The field of electronics is skyrocketing like never before. The habitat for the electronic components is a printed circuit board (PCB). With the advent of newer and finer technologies it has almost become impossible to detect the faults in a printed circuit board manually which consumes lot of manpower and time. This paper proposes a simple and cost effective method of fault diagnosis in a PCB using image processing techniques. In addition to fault detection and its classification this paper addresses various problems faced during the pre-processing phase. This paper overcomes the drawbacks of the previous works such as improper orientations of the image and size variations of the image. Basically image subtraction algorithm is used for fault detection. The most commonly occurring faults are concentrated in this work and the same are implemented using MATLAB tool.
Implementation of Picwords to Warping Pictures and Keywords through CalligramIRJET Journal
The document describes a system called PicWords that combines images with keywords. It has four main modules: 1) A picture module that takes an input image and generates a silhouette, patches the silhouette into regions, and ranks the patches. 2) A keywords module that collects and ranks keywords. 3) A picture and keywords module that maps keywords to patches. 4) A post-processing module that finalizes the output. The goal is to represent an image and convey additional information about it in a concise visual manner using integrated pictures and words.
IMAGE RECOGNITION USING MATLAB SIMULINK BLOCKSETIJCSEA Journal
The world over, image recognition are essential players in promoting quality object recognition especially in emergency and search-rescue operation. In this paper precise image recognition system using Matlab Simulink Blockset to detect selected object from crowd is presented. The process involves extracting object
features and then recognizes it considering illumination, direction and pose. A Simulink model has been developed to eliminate the tiny elements from the image, then creating segments for precise object recognition. Furthermore, the simulation explores image recognition from the coloured and gray-scale images through image processing techniques in Simulink environment. The tool employed for computation
and simulation is the Matlab image processing blockset. The process comprises morphological operation method which is effective for captured images and video. The results of extensive simulations indicate that this method is suitable for application identifying a person from a crow. The model can be used in emergency and search-rescue operation as well as in medicine, information security, access control, law enforcement, surveillance system, microscopy etc.
The model explains how we can Automate System using Artificial Intelligence.
It broadly concerns about:-
1. Lane Detection.
2. Traffic Sign Classification.
3. Behavioural Cloning.
IRJET - Automatic Licence Plate Detection and RecognitionIRJET Journal
This document describes a system for automatic license plate detection and recognition. The system uses image processing techniques in MATLAB to capture an image of a vehicle license plate, preprocess the image by converting it to grayscale and reducing noise, segment the license plate from the image, and recognize the characters on the plate using optical character recognition. The system is proposed to identify vehicles entering a university campus and check if they are registered in the university's database. The document outlines the methodology, which involves preprocessing, segmentation, character separation, and character recognition steps. It also discusses related work on license plate detection algorithms and presents experimental results demonstrating the system's ability to accurately extract license plate numbers from images.
IRJET- Automatic Traffic Sign Detection and Recognition using CNNIRJET Journal
This document presents a method for automatic traffic sign detection and recognition using convolutional neural networks (CNNs). The proposed system first enhances input images and performs thresholding and region extraction. Features are then extracted and the images are classified using a CNN. The CNN architecture includes convolutional, ReLU, pooling and fully connected layers. The system achieves detection rates over 88% mean average precision and boundary estimation errors under 3 pixels. It runs in real-time at over 7 frames per second on mobile platforms, providing accurate traffic sign detection, recognition and boundary estimation. The method is robust to occlusion, blurring and small targets compared to other methods.
This document discusses color detection using OpenCV in C++. It introduces color detection and OpenCV, with the objective of implementing object-oriented programming concepts to detect pixel colors in a 3-channel RGB image. The architecture involves OpenCV capturing images in BGR format. Implementation calculates spatial moments and central moments of a binary image to determine pixel colors. Future applications include computer vision, object segregation and tracking based on color.
IRJET- Identification of Scene Images using Convolutional Neural Networks - A...IRJET Journal
This document summarizes research on using convolutional neural networks (CNNs) for scene image identification. It first discusses traditional object detection methods and their limitations. CNNs are presented as an improved approach, with convolutional, pooling and fully connected layers to extract features and classify images. Several popular CNN-based object detection algorithms are then summarized, including R-CNN, Fast R-CNN, Faster R-CNN and YOLO. The document concludes that CNN methods provide more accurate object identification compared to traditional algorithms due to their ability to learn from large datasets.
An Image Based PCB Fault Detection and Its Classificationrahulmonikasharma
The field of electronics is skyrocketing like never before. The habitat for the electronic components is a printed circuit board (PCB). With the advent of newer and finer technologies it has almost become impossible to detect the faults in a printed circuit board manually which consumes lot of manpower and time. This paper proposes a simple and cost effective method of fault diagnosis in a PCB using image processing techniques. In addition to fault detection and its classification this paper addresses various problems faced during the pre-processing phase. This paper overcomes the drawbacks of the previous works such as improper orientations of the image and size variations of the image. Basically image subtraction algorithm is used for fault detection. The most commonly occurring faults are concentrated in this work and the same are implemented using MATLAB tool.
Hand gesture recognition using support vector machinetheijes
1) The document describes a system for hand gesture recognition using support vector machines. It uses Canny's edge detection algorithm and histogram of gradients (HOG) for feature extraction from input images of hand gestures.
2) The system is trained using a dataset of predefined hand gestures. During testing, it compares the features extracted from new input images to those in the training dataset and classifies the gesture using an SVM classifier.
3) Experimental results found the system could accurately recognize 20 different static hand gestures in complex backgrounds. However, the authors note that future work could focus on real-time gesture recognition and reducing complexity for faster processing.
Performance Evaluation of CNN Based Pedestrian and Cyclist Detectors On Degra...CSCJournals
This paper evaluates the effects of input image degradation on performance of image object detectors. The purpose of the evaluation is to determine usability of the detectors trained on original images in adverse conditions. SSD and Faster R-CNN based pedestrian and cyclist detector performance with images degraded with motion blur, out-of-focus blur, and JPEG compression artefacts, most commonly occurring in mobile or static traffic systems. An experiment was designed to assess the effect of degradations on detection precision and cross class confusion. The paper describes the two datasets created for this evaluation, evaluation of a number of detectors on increasingly more degraded images, comparison of their performance, and assessment of their tolerance to different types of image degradation as well as a discussion of the results.
This document discusses computer vision and robot vision. It describes early work using artificial neural networks to allow a robot to steer a vehicle based on camera images (ALVINN system). The document outlines the two main stages of robot vision: image processing and scene analysis. Image processing transforms raw images, e.g. through averaging, edge enhancement, and region finding algorithms. Scene analysis extracts task-specific information by interpreting lines, curves, and applying model-based approaches to reconstruct scenes from primitive 3D objects. Stereo vision obtains depth information through triangulation using two camera images.
IRJET- Implementation of Gender Detection with Notice Board using Raspberry PiIRJET Journal
1) The document describes a system that uses a Raspberry Pi device with a camera module to implement gender detection.
2) Images captured by the camera are processed through a convolutional neural network to extract facial features and predict gender.
3) The system is intended to address limitations of existing gender detection technologies and provide a low-cost hardware solution using a Raspberry Pi single-board computer.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Hardware software co simulation of edge detection for image processing system...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Adaptive membership functions for hand written character recognition by voron...JPINFOTECH JAYAPRAKASH
The document proposes a new adaptive membership function approach for handwritten character recognition using image zoning. Existing zoning methods use static, non-adaptive membership functions that cannot model local feature distributions. The proposed system introduces adaptive membership functions selected for each zone using a genetic algorithm. It determines the optimal zoning topology and adaptive membership functions in a single process. Experimental results show it performs better than traditional zoning methods.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
The document evaluates the performance of various foreground extraction algorithms for object detection in visual surveillance. It analyzes three background modeling techniques (change detection mask, median, histogram) and two background subtraction algorithms (frame difference, approximate median). Experimental results on test videos show that background modeling using the median value technique and background subtraction using frame differencing provides the most robust and efficient combination. Processing times are reported for different combinations of algorithms. The study concludes that the median-based approach has good computational efficiency and robustness for background modeling.
Digital Image Processing and Edge DetectionSeda Yalçın
This presentation is an introduction for digital image processing and edge detection which covers them on four topic; example of fields that use digital image processing, visibility that depends on human perception, fundamental definition of an image, analysis of edge detection algorithms such as Roberts, Prewitt, Sobel and Laplacian of a Gaussian.
Facial Expression Recognition Using SVM Classifierijeei-iaes
Facial feature tracking and facial actions recognition from image sequence attracted great attention in computer vision field. Computational facial expression analysis is a challenging research topic in computer vision. It is required by many applications such as human-computer interaction, computer graphic animation and automatic facial expression recognition. In recent years, plenty of computer vision techniques have been developed to track or recognize the facial activities in three levels. First, in the bottom level, facial feature tracking, which usually detects and tracks prominent landmarks surrounding facial components (i.e., mouth, eyebrow, etc), captures the detailed face shape information; Second, facial actions recognition, i.e., recognize facial action units (AUs) defined in FACS, try to recognize some meaningful facial activities (i.e., lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize some meaningful facial activities (i.e., lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize facial expressions that represent the human emotion states. In this proposed algorithm initially detecting eye and mouth, features of eye and mouth are extracted using Gabor filter, (Local Binary Pattern) LBP and PCA is used to reduce the dimensions of the features. Finally SVM is used to classification of expression and facial action units.
Ieee projects 2012 2013 - Digital Image ProcessingK Sundaresh Ka
ieee projects download, base paper for ieee projects, ieee projects list, ieee projects titles, ieee projects for cse, ieee projects on networking,ieee projects 2012, ieee projects 2013, final year project, computer science final year projects, final year projects for information technology, ieee final year projects, final year students projects, students projects in java, students projects download, students projects in java with source code, students projects architecture, free ieee papers
PCB Faults Detection Using Image Processingijceronline
This paper reviews the digital image processing for PCB fault detection by using MATLAB software. In this project we are implementing different algorithms in sequentional manner with GUI. In this process we are giving two input images one to be inspected for errors i.e. layout of circuit which is implemented on PCB and other one is reference image or standard image of PCB. After these process we can obtained numbers of faults in any respect like hole, Breakout etc. it helps to detect the fault at primary stage of designing. Hence to improve the image quality of compared image we use sharpened process, so we get sharpen images and fault can be detected easily and it is fast and accurate .it reduce the manufacturing cost of PCB
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
This document presents a Matlab-based automatic number plate recognition (ANPR) system that uses template matching for optical character recognition of license plates. The system captures images using a webcam, processes the images in Matlab to isolate characters, and recognizes the characters by comparing them to templates. It then communicates the results to a PIC microcontroller to control a motorized barrier. The system achieved a 90% character recognition success rate under optimal lighting conditions using this approach. Recommendations for improving processing speed include implementing the system on dedicated hardware like an FPGA or ASIC.
This document summarizes a research paper on face recognition that accounts for variations in pose, alignment, color, illumination, and expression. The paper proposes using a Pyramid Convolutional Neural Network (Pyramid CNN) which can learn face representations in a computationally efficient manner. The Pyramid CNN incorporates feature sharing across multi-scale face representations to increase discriminative ability. It also uses 3D alignment and color normalization to reduce the effects of pose, lighting, and color differences. Evaluation on the LFW database shows the Pyramid CNN approach achieves competitive recognition accuracy.
Final Year IEEE Project 2013-2014 - Digital Image Processing Project Title a...elysiumtechnologies
This document provides information about Elysium Technologies Private Limited, an Indian technology company with over 13 years of experience. It has branches across multiple cities in India and provides services such as automated services, 24/7 help desk support, and ticketing and appointment systems. The company has over 250 developers and 20 researchers on staff.
Enhanced Face Detection Based on Haar-Like and MB-LBP FeaturesDr. Amarjeet Singh
The effective real-time face detection framework
proposed by Viola and Jones gained much popularity due its
computational efficiency and its simplicity. A notable
variant replaces the original Haar-like features with MBLBP (Multi-Block Local Binary Pattern) which are defined
by the local binary pattern operator, both detector types are
integrated into the OpenCV library. However, each
descriptor and its evaluation method has its own set of
strengths and setbacks. In this paper, an enhanced two-layer
face detector composed of both Haar-like and MB-LBP
features is presented. Haar-like features are employed as a
coarse filter but with a new evaluation involving dual
threshold. The already established MB-LBPs are arranged
as the fine filter of the detector. The Gentle AdaBoost
learning algorithm is deployed for the training of the
proposed detector to reach the classification and
performance potential. Experiments show that in the early
stages of classification, Haar features with dual threshold
are more discriminative than MB-LBP and original Haarlike features with respect to number of features required
and computation. Benchmarking the proposed detector
demonstrate overall 12% higher detection rate at 17% false
alarm over using MB-LBP features singly while performing
with ×3 speedup.
Number Plate Recognition of Still Images in Vehicular Parking SystemIRJET Journal
This document discusses a proposed method for number plate recognition in vehicle parking systems using image processing techniques. It begins with an abstract that outlines the increasing need for automated vehicle management systems due to rising vehicle and traffic volumes. It then provides an overview of the key steps in number plate recognition systems - plate detection, character segmentation, and character recognition. The proposed method uses profile projection for segmentation and neural networks for recognition. The document reviews several existing plate detection methods and their limitations. It proposes a new method that uses edge detection and morphological operations to isolate the license plate from an image while removing noise. Finally, it discusses factors to consider for license plate detection and different image segmentation techniques used in existing automatic number plate recognition systems.
IRJET- Video Forgery Detection using Machine LearningIRJET Journal
This document proposes a method to detect video forgery using machine learning. It discusses extracting optical flow and GLCM features from video frames and using them to train a support vector machine classifier. The method segments video frames, applies k-means clustering to group similar regions, and extracts GLCM features for comparison. This allows the system to detect any duplicated or manipulated frames through feature analysis and machine learning classification.
IRJET - A Research on Video Forgery Detection using Machine LearningIRJET Journal
The document presents a research on detecting video forgery using machine learning. It proposes a novel approach that uses optical flow and coarse-to-fine detection strategy to detect copy-move image forgery in videos. The approach first divides video frames into overlapping blocks, then extracts GLCM features from blocks. It identifies duplicate blocks using k-means clustering and Euclidean distance calculation. Finally, it detects forged regions in frames by highlighting the duplicate blocks. The approach was implemented and experiments showed it could successfully detect forged regions in videos.
Hand gesture recognition using support vector machinetheijes
1) The document describes a system for hand gesture recognition using support vector machines. It uses Canny's edge detection algorithm and histogram of gradients (HOG) for feature extraction from input images of hand gestures.
2) The system is trained using a dataset of predefined hand gestures. During testing, it compares the features extracted from new input images to those in the training dataset and classifies the gesture using an SVM classifier.
3) Experimental results found the system could accurately recognize 20 different static hand gestures in complex backgrounds. However, the authors note that future work could focus on real-time gesture recognition and reducing complexity for faster processing.
Performance Evaluation of CNN Based Pedestrian and Cyclist Detectors On Degra...CSCJournals
This paper evaluates the effects of input image degradation on performance of image object detectors. The purpose of the evaluation is to determine usability of the detectors trained on original images in adverse conditions. SSD and Faster R-CNN based pedestrian and cyclist detector performance with images degraded with motion blur, out-of-focus blur, and JPEG compression artefacts, most commonly occurring in mobile or static traffic systems. An experiment was designed to assess the effect of degradations on detection precision and cross class confusion. The paper describes the two datasets created for this evaluation, evaluation of a number of detectors on increasingly more degraded images, comparison of their performance, and assessment of their tolerance to different types of image degradation as well as a discussion of the results.
This document discusses computer vision and robot vision. It describes early work using artificial neural networks to allow a robot to steer a vehicle based on camera images (ALVINN system). The document outlines the two main stages of robot vision: image processing and scene analysis. Image processing transforms raw images, e.g. through averaging, edge enhancement, and region finding algorithms. Scene analysis extracts task-specific information by interpreting lines, curves, and applying model-based approaches to reconstruct scenes from primitive 3D objects. Stereo vision obtains depth information through triangulation using two camera images.
IRJET- Implementation of Gender Detection with Notice Board using Raspberry PiIRJET Journal
1) The document describes a system that uses a Raspberry Pi device with a camera module to implement gender detection.
2) Images captured by the camera are processed through a convolutional neural network to extract facial features and predict gender.
3) The system is intended to address limitations of existing gender detection technologies and provide a low-cost hardware solution using a Raspberry Pi single-board computer.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Hardware software co simulation of edge detection for image processing system...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Adaptive membership functions for hand written character recognition by voron...JPINFOTECH JAYAPRAKASH
The document proposes a new adaptive membership function approach for handwritten character recognition using image zoning. Existing zoning methods use static, non-adaptive membership functions that cannot model local feature distributions. The proposed system introduces adaptive membership functions selected for each zone using a genetic algorithm. It determines the optimal zoning topology and adaptive membership functions in a single process. Experimental results show it performs better than traditional zoning methods.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
The document evaluates the performance of various foreground extraction algorithms for object detection in visual surveillance. It analyzes three background modeling techniques (change detection mask, median, histogram) and two background subtraction algorithms (frame difference, approximate median). Experimental results on test videos show that background modeling using the median value technique and background subtraction using frame differencing provides the most robust and efficient combination. Processing times are reported for different combinations of algorithms. The study concludes that the median-based approach has good computational efficiency and robustness for background modeling.
Digital Image Processing and Edge DetectionSeda Yalçın
This presentation is an introduction for digital image processing and edge detection which covers them on four topic; example of fields that use digital image processing, visibility that depends on human perception, fundamental definition of an image, analysis of edge detection algorithms such as Roberts, Prewitt, Sobel and Laplacian of a Gaussian.
Facial Expression Recognition Using SVM Classifierijeei-iaes
Facial feature tracking and facial actions recognition from image sequence attracted great attention in computer vision field. Computational facial expression analysis is a challenging research topic in computer vision. It is required by many applications such as human-computer interaction, computer graphic animation and automatic facial expression recognition. In recent years, plenty of computer vision techniques have been developed to track or recognize the facial activities in three levels. First, in the bottom level, facial feature tracking, which usually detects and tracks prominent landmarks surrounding facial components (i.e., mouth, eyebrow, etc), captures the detailed face shape information; Second, facial actions recognition, i.e., recognize facial action units (AUs) defined in FACS, try to recognize some meaningful facial activities (i.e., lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize some meaningful facial activities (i.e., lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize facial expressions that represent the human emotion states. In this proposed algorithm initially detecting eye and mouth, features of eye and mouth are extracted using Gabor filter, (Local Binary Pattern) LBP and PCA is used to reduce the dimensions of the features. Finally SVM is used to classification of expression and facial action units.
Ieee projects 2012 2013 - Digital Image ProcessingK Sundaresh Ka
ieee projects download, base paper for ieee projects, ieee projects list, ieee projects titles, ieee projects for cse, ieee projects on networking,ieee projects 2012, ieee projects 2013, final year project, computer science final year projects, final year projects for information technology, ieee final year projects, final year students projects, students projects in java, students projects download, students projects in java with source code, students projects architecture, free ieee papers
PCB Faults Detection Using Image Processingijceronline
This paper reviews the digital image processing for PCB fault detection by using MATLAB software. In this project we are implementing different algorithms in sequentional manner with GUI. In this process we are giving two input images one to be inspected for errors i.e. layout of circuit which is implemented on PCB and other one is reference image or standard image of PCB. After these process we can obtained numbers of faults in any respect like hole, Breakout etc. it helps to detect the fault at primary stage of designing. Hence to improve the image quality of compared image we use sharpened process, so we get sharpen images and fault can be detected easily and it is fast and accurate .it reduce the manufacturing cost of PCB
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
This document presents a Matlab-based automatic number plate recognition (ANPR) system that uses template matching for optical character recognition of license plates. The system captures images using a webcam, processes the images in Matlab to isolate characters, and recognizes the characters by comparing them to templates. It then communicates the results to a PIC microcontroller to control a motorized barrier. The system achieved a 90% character recognition success rate under optimal lighting conditions using this approach. Recommendations for improving processing speed include implementing the system on dedicated hardware like an FPGA or ASIC.
This document summarizes a research paper on face recognition that accounts for variations in pose, alignment, color, illumination, and expression. The paper proposes using a Pyramid Convolutional Neural Network (Pyramid CNN) which can learn face representations in a computationally efficient manner. The Pyramid CNN incorporates feature sharing across multi-scale face representations to increase discriminative ability. It also uses 3D alignment and color normalization to reduce the effects of pose, lighting, and color differences. Evaluation on the LFW database shows the Pyramid CNN approach achieves competitive recognition accuracy.
Final Year IEEE Project 2013-2014 - Digital Image Processing Project Title a...elysiumtechnologies
This document provides information about Elysium Technologies Private Limited, an Indian technology company with over 13 years of experience. It has branches across multiple cities in India and provides services such as automated services, 24/7 help desk support, and ticketing and appointment systems. The company has over 250 developers and 20 researchers on staff.
Enhanced Face Detection Based on Haar-Like and MB-LBP FeaturesDr. Amarjeet Singh
The effective real-time face detection framework
proposed by Viola and Jones gained much popularity due its
computational efficiency and its simplicity. A notable
variant replaces the original Haar-like features with MBLBP (Multi-Block Local Binary Pattern) which are defined
by the local binary pattern operator, both detector types are
integrated into the OpenCV library. However, each
descriptor and its evaluation method has its own set of
strengths and setbacks. In this paper, an enhanced two-layer
face detector composed of both Haar-like and MB-LBP
features is presented. Haar-like features are employed as a
coarse filter but with a new evaluation involving dual
threshold. The already established MB-LBPs are arranged
as the fine filter of the detector. The Gentle AdaBoost
learning algorithm is deployed for the training of the
proposed detector to reach the classification and
performance potential. Experiments show that in the early
stages of classification, Haar features with dual threshold
are more discriminative than MB-LBP and original Haarlike features with respect to number of features required
and computation. Benchmarking the proposed detector
demonstrate overall 12% higher detection rate at 17% false
alarm over using MB-LBP features singly while performing
with ×3 speedup.
Number Plate Recognition of Still Images in Vehicular Parking SystemIRJET Journal
This document discusses a proposed method for number plate recognition in vehicle parking systems using image processing techniques. It begins with an abstract that outlines the increasing need for automated vehicle management systems due to rising vehicle and traffic volumes. It then provides an overview of the key steps in number plate recognition systems - plate detection, character segmentation, and character recognition. The proposed method uses profile projection for segmentation and neural networks for recognition. The document reviews several existing plate detection methods and their limitations. It proposes a new method that uses edge detection and morphological operations to isolate the license plate from an image while removing noise. Finally, it discusses factors to consider for license plate detection and different image segmentation techniques used in existing automatic number plate recognition systems.
IRJET- Video Forgery Detection using Machine LearningIRJET Journal
This document proposes a method to detect video forgery using machine learning. It discusses extracting optical flow and GLCM features from video frames and using them to train a support vector machine classifier. The method segments video frames, applies k-means clustering to group similar regions, and extracts GLCM features for comparison. This allows the system to detect any duplicated or manipulated frames through feature analysis and machine learning classification.
IRJET - A Research on Video Forgery Detection using Machine LearningIRJET Journal
The document presents a research on detecting video forgery using machine learning. It proposes a novel approach that uses optical flow and coarse-to-fine detection strategy to detect copy-move image forgery in videos. The approach first divides video frames into overlapping blocks, then extracts GLCM features from blocks. It identifies duplicate blocks using k-means clustering and Euclidean distance calculation. Finally, it detects forged regions in frames by highlighting the duplicate blocks. The approach was implemented and experiments showed it could successfully detect forged regions in videos.
Analysis of Digital Image Forgery Detection using Adaptive Over-Segmentation ...IRJET Journal
This document proposes two methods for detecting forged regions in digital images: adaptive over-segmentation and feature point matching. Adaptive over-segmentation divides the host image into irregular, non-overlapping blocks to reduce computational complexity compared to overlapping blocks. Feature points are then extracted from each block using SIFT and matched between blocks to identify labeled feature points that indicate suspected forgery regions. Finally, a forgery region extraction algorithm processes the labeled feature points and applies morphological operations to detect the forged regions in the host image. The proposed methods aim to address limitations of prior blocked-based forgery detection techniques by improving efficiency and ability to handle geometric transformations of forged areas.
IRJET- Framework for Image Forgery DetectionIRJET Journal
The document proposes a framework for detecting image forgeries using optical flow and stable parameters. It begins with coarse detection to find suspected tampered points by analyzing optical flow sum consistency. Then it performs fine detection for precise location of forgeries, including duplicated frame pair matching based on optical flow correlation and validation checks to reduce false detections. The framework is designed to balance detection efficiency, robustness, and applicability.
An Enhanced Method to Detect Copy Move Forgey in Digital Image Processing usi...IRJET Journal
This document presents a study on detecting copy-move forgery in digital images. It discusses an enhanced method using 2D discrete wavelet transform (DWT) approach. The key steps of the proposed method include preprocessing, feature extraction using DWT, block matching to identify duplicated regions, and filtering to reduce false matches. The method aims to develop an efficient, robust technique for copy-move forgery detection. It reviews existing literature on various detection techniques in the intensity and frequency domains. The proposed method extracts DWT features and uses a block matching algorithm to detect duplicated regions more precisely compared to other methods.
IRJET - Kirsch Compass Kernel Edge Detection for Vehicle Number Plate Det...IRJET Journal
This document describes a method for vehicle number plate detection using image processing techniques. It involves preprocessing the captured vehicle image by converting it to grayscale and binary, then using Kirsch compass kernel edge detection to locate the number plate region. Morphological operations like dilation and erosion are performed for processing. The number plate is extracted using bounding box technique and characters within are segmented. Individual characters are displayed and can be recognized using template matching. The described method aims to accurately detect vehicle number plates for applications like parking access control.
An Efficient Image Forensic Mechanism using Super Pixel by SIFT and LFP Algor...IRJET Journal
This document summarizes a research paper that proposes an efficient image forensic mechanism using super pixels, scale-invariant feature transform (SIFT), and local fingerprint (LFP) algorithm to detect copy-move forgery. The mechanism applies wavelet decomposition to compute super pixel sizes for segmentation, extracts features using SIFT, and performs region growing to detect forged regions. Experimental results showed increased performance in precision, sensitivity, specificity, and F1 score measures for forgery detection compared to existing techniques. The document also reviews several related works on image forgery detection techniques.
Lane Detection and Traffic Sign Recognition using OpenCV and Deep Learning fo...IRJET Journal
This document discusses lane detection and traffic sign recognition methods for autonomous vehicles. It proposes using OpenCV and deep learning techniques for lane detection and a CNN model for traffic sign recognition. For lane detection, it describes using frame masking, image thresholding, and Hough line transformation on camera images to detect lane markings. For traffic sign recognition, it discusses pre-processing images, developing a CNN architecture called EdLeNet based on LeNet, and achieving over 98% accuracy on a test set for sign classification. The goal is to incorporate these computer vision methods into driver assistance systems to help enable safer autonomous driving.
IRJET - Face Recognition based Attendance SystemIRJET Journal
This document describes a face recognition-based attendance system. It begins with an introduction to face recognition and the challenges of implementing such a system in real-time. It then reviews related work on algorithms used for face detection (Haar cascade), feature extraction (Histogram of Oriented Gradients), and recognition (Convolutional Neural Networks). The proposed system is described as collecting a student database, extracting encodings from images using CNN, and comparing real-time detected faces to the database using HOG detection and Euclidean distance matching to mark attendance. Experimental results aimed to test recognition under different training, lighting, and pose conditions.
A New Deep Learning Based Technique To Detect Copy Move Forgery In Digital Im...IRJET Journal
This document proposes a new deep learning technique to detect copy move forgery in digital images. It uses a VGG16 CNN model to extract feature vectors from image blocks. Euclidean distance is used to measure similarity between feature vectors and detect matching blocks, indicating potential forgery. The proposed method is evaluated on the CoMoFoD dataset and achieves higher F1-scores than ResNet50 and EfficientNet models, detecting forged regions more accurately.
Licence Plate Recognition Using Supervised Learning and Deep LearningIRJET Journal
1. The document discusses using supervised learning and deep learning techniques for license plate recognition (LPR). It analyzes direct and indirect recognition algorithms and compares features of existing LPR systems.
2. A proposed LPR system is described that uses image preprocessing, license plate detection, character segmentation, and character recognition. Preprocessing improves image quality before detecting the license plate region.
3. The proposed system applies contour tracing and Canny edge detection algorithms to the license plate region to sharpen character edges for recognition.
Application of Digital Image Correlation: A ReviewIRJET Journal
This document reviews the application of digital image correlation (DIC) technique. DIC is a non-contact optical method used to measure full-field surface deformations and strains. It works by tracking random speckle patterns on a material's surface between images taken before and after deformation. The document discusses how DIC can be used to detect crack initiation in concrete, measure strain maps, and determine material properties like elastic modulus without being destructive. It also reviews several past studies where DIC was used to analyze strain in materials like gypsum, composites, and concrete. The document concludes that DIC provides an accurate alternative to conventional techniques and its use could be expanded in civil engineering.
Gear is a widely used mechanical component whose primary use is to transmit power from one shaft to
other. Gears are of many types namely spur gear, helical gears, worm gears etc. Gear drives are used in various
kinds of machines like automobiles, metal cutting tools, material handling equipment’s, rolling mills, marine
power plants etc. MATLAB is extensively used for scientific & research purposes. It is accurate & also has a
number of built in functions which makes it versatile. Gear Measurement has been carried out by focusing two
features of gear image object. The problems are to measure the gear features of gear image object, in the sense the
measurement of the area of the gear image object and as well the teeth of the gear will be counted. MATLAB tool
is used to develop a code which overcomes these problems and measures the area as well as teeth of the gear
image object counted.
IRJET- Matlab based Multi Feature Extraction in Image and Video Analysis ...IRJET Journal
This document discusses using MATLAB for multi-feature extraction in image and video analysis. It focuses on four techniques: 1) Improving image and video quality using histogram equalization, 2) Changing image and video formats, 3) Resizing images and videos, and 4) Compressing images and videos using wavelet compression techniques. It proposes combining these four techniques into one MATLAB-based software program to simplify image and video processing for users. The document reviews existing related work on individual techniques and argues the proposed approach integrates multiple techniques into a single tool.
This document describes an advanced document scanner that uses a phototransistor array instead of a CCD sensor to scan documents. It can also create a digital mosaic by stitching together multiple scanned images. The scanner works by using an array of phototransistors attached to an X-Y plotter to scan documents placed on a glass plate. The phototransistors detect light and send the data to a microcontroller for analog-to-digital conversion and then to MATLAB for digitization and mosaicing. Test results showed it could scan documents up to A2 size at 15 minutes per scan and create a mosaic by stitching two halved images back together.
Our life’s important part is Image. Without disturbing its overall structure of images, we can
remove the unwanted part of image with the help of image inpainting. There is simpler the inpainting of
the low resolution images than that of the high resolution images. In this system low resolution image
contained in different super resolution image inpainting methodologies and there are combined all these
methodologies to form the highly in painted image results. For this reason our system uses the super
resolution algorithm which is responsiblefor inpainting of singleimage.
LANE DETECTION USING IMAGE PROCESSING IN PYTHONIRJET Journal
This document presents a lane detection method using image processing techniques in Python. It involves Gaussian smoothing, Canny edge detection, region masking of the road area, and Hough transform to detect lane lines. The key steps are preprocessing the image, extracting edges, selecting the road region, and applying Hough transform to detect prominent lines corresponding to the lane markings. Experimental results on test images and videos demonstrate the effectiveness of the approach for lane detection without using complex deep learning methods. Some limitations around noise and variations in road conditions are also discussed.
Rotation Invariant Face Recognition using RLBP, LPQ and CONTOURLET TransformIRJET Journal
This document discusses rotation invariant face recognition using three feature extraction techniques: Rotated Local Binary Pattern (RLBP), Local Phase Quantization (LPQ), and Contourlet transform. It first extracts features from input face images using these three techniques. It then applies Linear Discriminant Analysis to reduce the feature dimensions. Finally, it uses k-Nearest Neighbors classification to perform face recognition on the Jaffe dataset. Experimental results show that the face recognition accuracy without LDA is 99.06% and increases to 100% when LDA is used for feature dimension reduction.
IRJET - Computer Vision-based Image Processing System for Redundant Objec...IRJET Journal
This document describes a proposed computer vision-based image processing system for detecting redundant objects using a Raspberry Pi. The system would utilize a Raspberry Pi connected to a USB camera to capture video frames and detect motion using OpenCV image processing libraries. When motion is detected, the system would segment the moving object from the background using thresholding techniques and morphological operations. It would then highlight and track the detected object using contour functions. Detected objects would be sent to a monitoring interface along with an alert to allow remote monitoring and response. The system aims to provide low-cost real-time surveillance and intruder detection capabilities.
IRJET - Computer-Assisted ALL, AML, CLL, CML Detection and Counting for D...IRJET Journal
This document describes a computer-assisted method for detecting and counting four types of blood cancer (ALL, AML, CLL, CML) from microscopic blood images. The method first segments the image to identify white blood cells, then extracts lymphocytes. Shape and color features of the lymphocytes are used to classify them as normal or blast cells using SVM. The system was found to be more accurate and fast compared to manual identification methods. It aims to automatically diagnose blood cancers from images in a time-efficient and accurate manner.
Similar to IRJET- Image Forgery Detection using Support Vector Machine (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.