To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Nanotechnology involves controlling material structures at the molecular level to build devices with positional control at the atomic scale. It allows for self-assembly and could enable atom computers, intelligent vehicles, military and medical applications through precisely arranging molecules. While nanotechnology promises benefits like low-cost production and miniaturization, challenges include testing billion-molecule circuits and ensuring programmability at the nanoscale. Experimental and theoretical work is progressing to realize potential applications in materials, devices, and tools for nanotechnology.
OOFELIE::Multiphysics is a 3D multiphysics simulation software that allows for the design and analysis of microsystems, such as MEMS and MOEMS devices. It uses strongly coupled finite element analysis to obtain accurate results for increasingly smaller components in a timely manner. The software automates design space exploration through parametric studies and optimization to identify the best design. It also links with CAD and EDA tools to facilitate the design flow from concept to fabrication. OOFELIE::Multiphysics was used by ONERA to simulate a vibrating inertial accelerometer and optimize its performance.
Coventor is organizing a free two-day seminar and training event on MEMS and IC co-design tools from May 17-18, 2010 in Paris. Day one will feature a conference with speakers from companies like STMicroelectronics discussing topics like MEMS-IC co-design and energy harvesting. Day two will provide hands-on training for MEMS+, a co-simulation platform for MEMS and integrated circuits, including an accelerometer design exercise. Attendance is free but registration is required as space is limited.
Analog signal processing approach for coarse and fine depth estimationsipij
This document discusses an analog signal processing approach for coarse and fine depth estimation using stereo image pairs. It proposes modifications to existing normalized cross correlation (NCC) and sum absolute differences (SAD) stereo correspondence algorithms to reduce computation time. For the NCC algorithm, it suggests using only the diagonal elements of image blocks to compute correlation, reducing computations from 2D to 1D. For hardware implementation, it presents a new imaging architecture with parallel analog and digital systems, where the analog system performs the computationally intensive NCC algorithm on sensor data in real-time to reduce overall processing time compared to digital-only systems. Experimental results show the modified algorithms can achieve faster computation speeds without compromising performance.
Binduhasini Sairamesh is an electrical engineer seeking new opportunities. She has over 10 years of experience in research, teaching, and engineering projects. Some of her qualifications include an MS in electrical engineering, experience developing algorithms for autonomous vehicles, implementing neural networks for image processing, and teaching at the university level. She is proficient in languages like C, C++, Verilog and has worked on projects involving digital logic design, signal processing, and FPGA implementations.
This document discusses the design and implementation of a fire detection system using computer vision. It proposes using a system with multiple units including a motion detecting unit, color analyzing unit, computing unit, verifying unit, location unit, and alarm unit. Different algorithms are considered for fire detection including color-based approaches, motion-based approaches, and approaches using fuzzy logic and hidden Markov models. The system is intended to automatically identify and locate fires as part of a larger surveillance system with benefits of being cheaper and more accurate than existing sensor-based solutions.
The document discusses using region-based techniques for process discovery from event logs. It proposes incorporating region information into cycle detection algorithms to more efficiently identify complex cycles when constructing an automaton from event traces. This enables better application of region-based techniques to discover process models from industrial event logs. The experimental results suggest the techniques can significantly improve applying region theory for process mining in industry scenarios.
The student completed three co-op terms at Eastman Chemical Company in electrical engineering. In plant engineering, they worked on projects involving engineering drawings and wrote interlock test procedures. In control systems, they created a human machine interface for operators and implemented logic between it and a PLC. In electric utilities, they coordinated protective devices, processed connection requests, modeled power systems, and ensured compliance with electrical standards.
Nanotechnology involves controlling material structures at the molecular level to build devices with positional control at the atomic scale. It allows for self-assembly and could enable atom computers, intelligent vehicles, military and medical applications through precisely arranging molecules. While nanotechnology promises benefits like low-cost production and miniaturization, challenges include testing billion-molecule circuits and ensuring programmability at the nanoscale. Experimental and theoretical work is progressing to realize potential applications in materials, devices, and tools for nanotechnology.
OOFELIE::Multiphysics is a 3D multiphysics simulation software that allows for the design and analysis of microsystems, such as MEMS and MOEMS devices. It uses strongly coupled finite element analysis to obtain accurate results for increasingly smaller components in a timely manner. The software automates design space exploration through parametric studies and optimization to identify the best design. It also links with CAD and EDA tools to facilitate the design flow from concept to fabrication. OOFELIE::Multiphysics was used by ONERA to simulate a vibrating inertial accelerometer and optimize its performance.
Coventor is organizing a free two-day seminar and training event on MEMS and IC co-design tools from May 17-18, 2010 in Paris. Day one will feature a conference with speakers from companies like STMicroelectronics discussing topics like MEMS-IC co-design and energy harvesting. Day two will provide hands-on training for MEMS+, a co-simulation platform for MEMS and integrated circuits, including an accelerometer design exercise. Attendance is free but registration is required as space is limited.
Analog signal processing approach for coarse and fine depth estimationsipij
This document discusses an analog signal processing approach for coarse and fine depth estimation using stereo image pairs. It proposes modifications to existing normalized cross correlation (NCC) and sum absolute differences (SAD) stereo correspondence algorithms to reduce computation time. For the NCC algorithm, it suggests using only the diagonal elements of image blocks to compute correlation, reducing computations from 2D to 1D. For hardware implementation, it presents a new imaging architecture with parallel analog and digital systems, where the analog system performs the computationally intensive NCC algorithm on sensor data in real-time to reduce overall processing time compared to digital-only systems. Experimental results show the modified algorithms can achieve faster computation speeds without compromising performance.
Binduhasini Sairamesh is an electrical engineer seeking new opportunities. She has over 10 years of experience in research, teaching, and engineering projects. Some of her qualifications include an MS in electrical engineering, experience developing algorithms for autonomous vehicles, implementing neural networks for image processing, and teaching at the university level. She is proficient in languages like C, C++, Verilog and has worked on projects involving digital logic design, signal processing, and FPGA implementations.
This document discusses the design and implementation of a fire detection system using computer vision. It proposes using a system with multiple units including a motion detecting unit, color analyzing unit, computing unit, verifying unit, location unit, and alarm unit. Different algorithms are considered for fire detection including color-based approaches, motion-based approaches, and approaches using fuzzy logic and hidden Markov models. The system is intended to automatically identify and locate fires as part of a larger surveillance system with benefits of being cheaper and more accurate than existing sensor-based solutions.
The document discusses using region-based techniques for process discovery from event logs. It proposes incorporating region information into cycle detection algorithms to more efficiently identify complex cycles when constructing an automaton from event traces. This enables better application of region-based techniques to discover process models from industrial event logs. The experimental results suggest the techniques can significantly improve applying region theory for process mining in industry scenarios.
The student completed three co-op terms at Eastman Chemical Company in electrical engineering. In plant engineering, they worked on projects involving engineering drawings and wrote interlock test procedures. In control systems, they created a human machine interface for operators and implemented logic between it and a PLC. In electric utilities, they coordinated protective devices, processed connection requests, modeled power systems, and ensured compliance with electrical standards.
El documento contiene información sobre diferentes herramientas de ofimática como hoja de cálculo, presentaciones, correo electrónico y Skype. Explica funciones básicas como formato condicional, uso de fórmulas, creación de gráficos estadísticos e inserción de objetos en las diapositivas. También describe cómo configurar y enviar correo electrónico, así como realizar conversaciones en Skype.
The strategy entails taking a paired position by going long on SBIN stock and short on the Bank Nifty index. SBIN and Bank Nifty are highly correlated but SBIN has recently underperformed, creating an opportunity. The strategy expects SBIN to outperform over the short to medium term, aiming to profit as the price ratio between SBIN and Bank Nifty reverts to the mean. The targeted profit is Rs. 30,000 with a stop loss of Rs. 13,000 and approximate investment of Rs. 1,16,000 over a 15-20 day holding period.
The document promotes network marketing as a way to gain more financial freedom and flexibility through additional monthly income. It discusses challenges many face with debt, unemployment, and retirement uncertainty. Network marketing is presented as a low-cost, flexible opportunity to build residual income through recruiting others and receiving commissions on product sales.
modelo didactico de integracion de las Ticsguest141d8b
El documento lista varios programas de software libre que la UNED podría utilizar para integrar las TIC, incluyendo el navegador Firefox, el cliente de correo Thunderbird, el editor de páginas web NVU, el programa de edición de imágenes GIMP, el paquete ofimático OpenOffice, la plataforma de aprendizaje en línea Moodle, herramientas de mapas conceptuales como Freemind y JavaClic, programas de audio y video como Audacity y Rock you, programas de diseño como Xara, programas de comunicación como Skype y
Grant Marketing On Video provides video marketing services to help businesses succeed in today's complex digital landscape dominated by video. Videos account for over half of all internet traffic and are much more likely to appear on the first page of search results, making video an important part of online marketing strategies. Customers are encouraged to view the next slide for additional details on Grant Marketing On Video's video marketing services.
This document invites students to a QFIN Meet & Greet on Friday, April 6 from 9:30-10:30 am in Showker 242. Attendees can mingle with Finance faculty, advisors, and other QFIN majors over coffee and pastries. The informal session allows students to learn about related student organizations, seek career guidance, and ask questions about course scheduling.
Este documento contiene información sobre un plan de lección para una asignatura de álgebra para estudiantes de primer año de bachillerato. Incluye los objetivos, contenidos, metodología, recursos, tiempo y evaluación de la unidad sobre factorización de expresiones algebraicas. También incluye formatos para registrar datos de estudiantes, asistencia y control escolar.
Informe sobre-el-mercado-inmobiliario-de-barcelona-t3-y-t4-de-2011Lucas Fox
El informe resume las condiciones del mercado inmobiliario de Barcelona en el tercer y cuarto trimestre de 2011. Las ventas y alquileres de propiedades se mantuvieron estables a lo largo del año a pesar de pequeñas caídas mensuales en los precios. Los precios de venta terminaron el año ligeramente más bajos que a finales de 2010, mientras que la demanda de alquileres de corta estancia permaneció fuerte debido al crecimiento continuo del turismo en la ciudad.
Este documento presenta información sobre diferentes conceptos de probabilidad, incluyendo tiro al blanco, motobombas, bombillos y dados. Explica cómo calcular probabilidades subjetivas, frecuenciales y clásicas para diferentes escenarios, y cómo construir un espacio muestral para identificar todos los resultados posibles y sus probabilidades asociadas. También analiza datos de frecuencias de pernos para identificar cuáles tienen mayores tasas de error.
The document contains contact information for an airline. It lists the word "Airline" and a contact phone number of 987466321. The brief document appears to be providing contact details for an airline customer service line.
This document contains credits for various photographers who contributed photos to a Haiku Deck presentation on SlideShare. The photographers credited include Luiz Fernando, Sonia Maria, Big Max Power, Jose Javier Martin Espartosa, chooyutshing, jonashaffer, John Romero, consonni consonni, | Tico|, Presidencia del Gobierno, gnuckx, Inti, ANSESGOB, BIDTransporte, Claudio.Ar, Dave Hamster, and todosnuestrosmuertos. The document ends by encouraging the reader to create their own Haiku Deck presentation.
This document provides gift ideas for different types of foodies and chefs. It describes gifts such as bento lunch boxes, serving spoons for amuse-bouches, onion goggles to prevent tears while cooking, a raclette grill for melting cheeses, and peanut butter cups. It also mentions cocktail shakers and martini glasses as gifts for bartenders. The gifts range in price from $10 to $54.50 and can be purchased from stores like Sur La Table or online retailers.
Analog signal processing approach for coarse and fine depth estimationsipij
Imaging and Image sensors is a field that is continuously evolving. There are new products coming into the
market every day. Some of these have very severe Size, Weight and Power constraints whereas other
devices have to handle very high computational loads. Some require both these conditions to be met
simultaneously. Current imaging architectures and digital image processing solutions will not be able to
meet these ever increasing demands. There is a need to develop novel imaging architectures and image
processing solutions to address these requirements. In this work we propose analog signal processing as a
solution to this problem. The analog processor is not suggested as a replacement to a digital processor but
it will be used as an augmentation device which works in parallel with the digital processor, making the
system faster and more efficient. In order to show the merits of analog processing two stereo
correspondence algorithms are implemented. We propose novel modifications to the algorithms and new
imaging architectures which, significantly reduces the computation time
Computer Vision-Based Early Fire Detection Using Machine LearningIRJET Journal
This document presents a computer vision-based system for early fire detection using machine learning. It captures video using a webcam and processes the frames to detect fire. The frames are converted to different color models and compared using OpenCV. Morphological transformations and thresholding are applied to detect fire regions. If fire is detected, an alarm is triggered and a notification email is sent. The system aims to reduce limitations of conventional fire detection methods and optimize detection using image processing techniques. A literature review is also presented discussing previous works on fire detection using computer vision and machine learning.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
1) The document proposes analog signal processing as a solution to reduce computation time for image alignment algorithms that have high computational loads.
2) It modifies the Normalized Cross Correlation (NCC) algorithm for image alignment by only using the diagonal elements of the template and reference image blocks to calculate correlation. This reduces computations compared to using all pixels.
3) A new imaging architecture is proposed that uses an analog processor to implement the modified NCC algorithm in parallel with digital image acquisition, providing faster computation.
Recognition and tracking moving objects using moving camera in complex scenesIJCSEA Journal
1) The document proposes a method for tracking moving objects in videos captured using a moving camera in complex scenes. It involves video stabilization, key frame extraction, object detection/tracking using Gaussian mixture models and Kalman filters, and object recognition using bag of features.
2) Key frame extraction identifies important frames for processing by computing edge differences between frames and selecting frames above a threshold.
3) Moving objects are detected using background subtraction and Gaussian mixture models, and then tracked across frames using Kalman filters.
4) Object recognition is performed using bag of features, which represents objects as histograms of visual word frequencies to classify objects based on characteristic visual parts.
IRJET - An Robust and Dynamic Fire Detection Method using Convolutional N...IRJET Journal
This document proposes a new fire detection method using convolutional neural networks (CNNs). Specifically, it uses the YOLOv3 object detection algorithm, which can detect objects like fire in images or videos quickly and accurately. The proposed method aims to reduce computational time and costs compared to other CNN-based approaches, while also improving detection accuracy and reducing false alarms. It discusses implementing the method using four main modules: data exploration, pre-processing, feature engineering, and model selection. The workflow involves exploring data, pre-processing images, extracting features, and selecting the YOLOv3 CNN model for fire detection. The goal is to develop a robust and dynamic fire detection system using computer vision techniques to help prevent accidents.
El documento contiene información sobre diferentes herramientas de ofimática como hoja de cálculo, presentaciones, correo electrónico y Skype. Explica funciones básicas como formato condicional, uso de fórmulas, creación de gráficos estadísticos e inserción de objetos en las diapositivas. También describe cómo configurar y enviar correo electrónico, así como realizar conversaciones en Skype.
The strategy entails taking a paired position by going long on SBIN stock and short on the Bank Nifty index. SBIN and Bank Nifty are highly correlated but SBIN has recently underperformed, creating an opportunity. The strategy expects SBIN to outperform over the short to medium term, aiming to profit as the price ratio between SBIN and Bank Nifty reverts to the mean. The targeted profit is Rs. 30,000 with a stop loss of Rs. 13,000 and approximate investment of Rs. 1,16,000 over a 15-20 day holding period.
The document promotes network marketing as a way to gain more financial freedom and flexibility through additional monthly income. It discusses challenges many face with debt, unemployment, and retirement uncertainty. Network marketing is presented as a low-cost, flexible opportunity to build residual income through recruiting others and receiving commissions on product sales.
modelo didactico de integracion de las Ticsguest141d8b
El documento lista varios programas de software libre que la UNED podría utilizar para integrar las TIC, incluyendo el navegador Firefox, el cliente de correo Thunderbird, el editor de páginas web NVU, el programa de edición de imágenes GIMP, el paquete ofimático OpenOffice, la plataforma de aprendizaje en línea Moodle, herramientas de mapas conceptuales como Freemind y JavaClic, programas de audio y video como Audacity y Rock you, programas de diseño como Xara, programas de comunicación como Skype y
Grant Marketing On Video provides video marketing services to help businesses succeed in today's complex digital landscape dominated by video. Videos account for over half of all internet traffic and are much more likely to appear on the first page of search results, making video an important part of online marketing strategies. Customers are encouraged to view the next slide for additional details on Grant Marketing On Video's video marketing services.
This document invites students to a QFIN Meet & Greet on Friday, April 6 from 9:30-10:30 am in Showker 242. Attendees can mingle with Finance faculty, advisors, and other QFIN majors over coffee and pastries. The informal session allows students to learn about related student organizations, seek career guidance, and ask questions about course scheduling.
Este documento contiene información sobre un plan de lección para una asignatura de álgebra para estudiantes de primer año de bachillerato. Incluye los objetivos, contenidos, metodología, recursos, tiempo y evaluación de la unidad sobre factorización de expresiones algebraicas. También incluye formatos para registrar datos de estudiantes, asistencia y control escolar.
Informe sobre-el-mercado-inmobiliario-de-barcelona-t3-y-t4-de-2011Lucas Fox
El informe resume las condiciones del mercado inmobiliario de Barcelona en el tercer y cuarto trimestre de 2011. Las ventas y alquileres de propiedades se mantuvieron estables a lo largo del año a pesar de pequeñas caídas mensuales en los precios. Los precios de venta terminaron el año ligeramente más bajos que a finales de 2010, mientras que la demanda de alquileres de corta estancia permaneció fuerte debido al crecimiento continuo del turismo en la ciudad.
Este documento presenta información sobre diferentes conceptos de probabilidad, incluyendo tiro al blanco, motobombas, bombillos y dados. Explica cómo calcular probabilidades subjetivas, frecuenciales y clásicas para diferentes escenarios, y cómo construir un espacio muestral para identificar todos los resultados posibles y sus probabilidades asociadas. También analiza datos de frecuencias de pernos para identificar cuáles tienen mayores tasas de error.
The document contains contact information for an airline. It lists the word "Airline" and a contact phone number of 987466321. The brief document appears to be providing contact details for an airline customer service line.
This document contains credits for various photographers who contributed photos to a Haiku Deck presentation on SlideShare. The photographers credited include Luiz Fernando, Sonia Maria, Big Max Power, Jose Javier Martin Espartosa, chooyutshing, jonashaffer, John Romero, consonni consonni, | Tico|, Presidencia del Gobierno, gnuckx, Inti, ANSESGOB, BIDTransporte, Claudio.Ar, Dave Hamster, and todosnuestrosmuertos. The document ends by encouraging the reader to create their own Haiku Deck presentation.
This document provides gift ideas for different types of foodies and chefs. It describes gifts such as bento lunch boxes, serving spoons for amuse-bouches, onion goggles to prevent tears while cooking, a raclette grill for melting cheeses, and peanut butter cups. It also mentions cocktail shakers and martini glasses as gifts for bartenders. The gifts range in price from $10 to $54.50 and can be purchased from stores like Sur La Table or online retailers.
Analog signal processing approach for coarse and fine depth estimationsipij
Imaging and Image sensors is a field that is continuously evolving. There are new products coming into the
market every day. Some of these have very severe Size, Weight and Power constraints whereas other
devices have to handle very high computational loads. Some require both these conditions to be met
simultaneously. Current imaging architectures and digital image processing solutions will not be able to
meet these ever increasing demands. There is a need to develop novel imaging architectures and image
processing solutions to address these requirements. In this work we propose analog signal processing as a
solution to this problem. The analog processor is not suggested as a replacement to a digital processor but
it will be used as an augmentation device which works in parallel with the digital processor, making the
system faster and more efficient. In order to show the merits of analog processing two stereo
correspondence algorithms are implemented. We propose novel modifications to the algorithms and new
imaging architectures which, significantly reduces the computation time
Computer Vision-Based Early Fire Detection Using Machine LearningIRJET Journal
This document presents a computer vision-based system for early fire detection using machine learning. It captures video using a webcam and processes the frames to detect fire. The frames are converted to different color models and compared using OpenCV. Morphological transformations and thresholding are applied to detect fire regions. If fire is detected, an alarm is triggered and a notification email is sent. The system aims to reduce limitations of conventional fire detection methods and optimize detection using image processing techniques. A literature review is also presented discussing previous works on fire detection using computer vision and machine learning.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
1) The document proposes analog signal processing as a solution to reduce computation time for image alignment algorithms that have high computational loads.
2) It modifies the Normalized Cross Correlation (NCC) algorithm for image alignment by only using the diagonal elements of the template and reference image blocks to calculate correlation. This reduces computations compared to using all pixels.
3) A new imaging architecture is proposed that uses an analog processor to implement the modified NCC algorithm in parallel with digital image acquisition, providing faster computation.
Recognition and tracking moving objects using moving camera in complex scenesIJCSEA Journal
1) The document proposes a method for tracking moving objects in videos captured using a moving camera in complex scenes. It involves video stabilization, key frame extraction, object detection/tracking using Gaussian mixture models and Kalman filters, and object recognition using bag of features.
2) Key frame extraction identifies important frames for processing by computing edge differences between frames and selecting frames above a threshold.
3) Moving objects are detected using background subtraction and Gaussian mixture models, and then tracked across frames using Kalman filters.
4) Object recognition is performed using bag of features, which represents objects as histograms of visual word frequencies to classify objects based on characteristic visual parts.
IRJET - An Robust and Dynamic Fire Detection Method using Convolutional N...IRJET Journal
This document proposes a new fire detection method using convolutional neural networks (CNNs). Specifically, it uses the YOLOv3 object detection algorithm, which can detect objects like fire in images or videos quickly and accurately. The proposed method aims to reduce computational time and costs compared to other CNN-based approaches, while also improving detection accuracy and reducing false alarms. It discusses implementing the method using four main modules: data exploration, pre-processing, feature engineering, and model selection. The workflow involves exploring data, pre-processing images, extracting features, and selecting the YOLOv3 CNN model for fire detection. The goal is to develop a robust and dynamic fire detection system using computer vision techniques to help prevent accidents.
Coronary heart disease is a disease with the highest mortality rates in the world. This makes the development of the diagnostic system as a very interesting topic in the field of biomedical informatics, aiming to detect whether a heart is normal or not. In the literature there are diagnostic system models by combining dimension reduction and data mining techniques. Unfortunately, there are no review papers that discuss and analyze the themes to date. This study reviews articles within the period 2009-2016, with a focus on dimension reduction methods and data mining techniques, validated using a dataset of UCI repository. Methods of dimension reduction use feature selection and feature extraction techniques, while data mining techniques include classification, prediction, clustering, and association rules.
Key frame extraction is an essential technique in the computer vision field. The extracted key frames should brief the salient events with an excellent feasibility, great efficiency, and with a high-level of robustness. Thus, it is not an easy problem to solve because it is attributed to many visual features. This paper intends to solve this problem by investigating the relationship between these features detection and the accuracy of key frames extraction techniques using TRIZ. An improved algorithm for key frame extraction was then proposed based on an accumulative optical flow with a self-adaptive threshold (AOF_ST) as recommended in TRIZ inventive principles. Several video shots including original and forgery videos with complex conditions are used to verify the experimental results. The comparison of our results with the-state-of-the-art algorithms results showed that the proposed extraction algorithm can accurately brief the videos and generated a meaningful compact count number of key frames. On top of that, our proposed algorithm achieves 124.4 and 31.4 for best and worst case in KTH dataset extracted key frames in terms of compression rate, while the-state-of-the-art algorithms achieved 8.90 in the best case.
Real Time Implementation of Ede Detection Technique for Angiogram Images on FPGAIRJET Journal
This document presents a new edge detection algorithm for angiogram images and its implementation on an FPGA. It begins with an introduction to angiography and importance of edge detection in analyzing angiogram images. It then describes the proposed algorithm which includes histogram equalization for enhancement followed by a modified Canny edge detection approach. The key steps of the modified Canny approach are also outlined. Experimental results on angiogram images demonstrate that the proposed FPGA implementation takes only 0.562ms for execution while maintaining accuracy. In conclusion, the algorithm is able to efficiently detect blood vessel edges in angiogram images making it useful for analyzing vascular diseases.
Detection of a user-defined object in an image using feature extraction- Trai...IRJET Journal
The document proposes a method for detecting user-defined objects in images using feature extraction and training. The method combines contour detection, edge detection, k-means clustering, color identification, and image segmentation. It uses an original "source" object image to train the system to recognize and identify the target object in other images based on a feature set. The key steps include pre-processing images, extracting features like contours and edges, using k-means clustering to identify colors, and analyzing color and shape features to detect matching objects. The results demonstrate the ability to accurately detect target objects against complex backgrounds.
IRJET- A Hybrid Approach for Fire Safety Intensives Automatic Assistance ...IRJET Journal
This document presents a hybrid approach for an automatic fire safety assistance system. It proposes extracting frames from video to convert to images, then using edge detection and image segmentation to separate the foreground fire from the background. Features are then extracted using 7 rules to identify fire pixels based on their color space values. Color detection is used to isolate pixels meeting thresholds for red, green, and blue channel values as well as saturation to accurately identify flame pixels despite lighting conditions. The system aims to provide early fire detection to minimize damage through computer vision techniques.
Forest Fire Detection Using Deep Learning and Image RecognitionIRJET Journal
This document describes a proposed system for forest fire detection using deep learning and image recognition techniques. The system aims to build a more accurate fire detection model using a customized VGG16 convolutional neural network. It involves collecting fire and non-fire images to train and test the model. The proposed system is expected to achieve higher accuracy than existing sensor-based systems by directly analyzing images to classify fires versus other heat sources.
IRJET - Object Identification in Steel Container through Thermal Image Pi...IRJET Journal
Thermal images of a steel container containing different objects were captured using a thermal camera. The images were filtered to remove noise and then segmented into clusters based on pixel differences, as different materials have unique thermal signatures. A pixel difference matrix map was calculated and feature vectors were extracted from scatter plots of pixel values. Average feature vector values can be used as a reference standard to identify objects inside steel containers based on their thermal properties.
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.
Corrosion Detection Using A.I : A Comparison of Standard Computer Vision Tech...csandit
In this paper we present a comparison between stand
ard computer vision techniques and Deep
Learning approach for automatic metal corrosion (ru
st) detection. For the classic approach, a
classification based on the number of pixels contai
ning specific red components has been
utilized. The code written in Python used OpenCV li
braries to compute and categorize the
images. For the Deep Learning approach, we chose Ca
ffe, a powerful framework developed at
“Berkeley Vision and Learning Center” (BVLC). The
test has been performed by classifying
images and calculating the total accuracy for the t
wo different approaches.
CORROSION DETECTION USING A.I. : A COMPARISON OF STANDARD COMPUTER VISION TEC...cscpconf
In this paper we present a comparison between standard computer vision techniques and Deep
Learning approach for automatic metal corrosion (rust) detection. For the classic approach, a
classification based on the number of pixels containing specific red components has been
utilized. The code written in Python used OpenCV libraries to compute and categorize the
images. For the Deep Learning approach, we chose Caffe, a powerful framework developed at
“Berkeley Vision and Learning Center” (BVLC). The test has been performed by classifying
images and calculating the total accuracy for the two different approaches.
Sensor Fault Detection in IoT System Using Machine LearningIRJET Journal
This document summarizes research on using machine learning techniques for sensor fault detection in IoT systems. The researchers collected temperature and humidity data from a DHT22 sensor and injected drift faults using an Arduino microcontroller. They extracted time-domain features from the normal and faulty signals and used them to train classifiers like artificial neural networks, support vector machines, naive Bayes, k-nearest neighbors, and decision trees. The trained models detected drift faults in the sensor output in real-time on an ESP8266 device. Support vector machines and artificial neural networks achieved the best performance based on accuracy, recall, F1-score metrics. The lightweight system demonstrates potential for low-cost, real-time sensor fault detection using machine learning.
The document proposes two video quality assessment models - a full-reference model that measures structural distortion compared to traditional error-based methods, and a no-reference model for compressed MPEG video. Experimental results on standard test datasets show the full-reference model has higher correlation with subjective quality ratings than previous methods. Preliminary results also show the no-reference model correlates well with the full-reference model for MPEG videos at different bitrates. The models analyze factors like quantization errors, blocking effects, and motion to evaluate video quality.
The International Journal of Engineering and Science (The IJES)theijes
This document summarizes and compares different techniques for moving object detection in video surveillance systems. It discusses background subtraction, background estimation, and adaptive contrast change detection methods. It finds that while traditional methods work for single objects, correlation between frames performs better for multiple objects or poor lighting conditions, as it detects changes between frames. The document evaluates several algorithms and concludes correlation significantly improves output and performance even with multiple moving objects, making it suitable for night-time surveillance applications.
Hardware Unit for Edge Detection with Comparative Analysis of Different Edge ...paperpublications3
Abstract: An edge in an image is a contour across which the brightness of the image changes abruptly. In image processing, an edge is often interpreted as one class of singularities. Edge detection is an important task in image processing. It is a main tool in pattern recognition, image segmentation, and scene analysis. An edge detector is basically a high pass filter that can be applied to extract the edge points in an image. This topic has attracted many researchers and many achievements have been made. Many researchers provided different approaches based on mathematical calculations which some of them are either robust or cost effective. A new algorithm will be proposed to detect the edges of image with increased robustness and throughput. Using this algorithm we will reduce the time complexity problem which is faced by previous algorithm. We will also propose hardware unit for proposed algorithm which will reduce the area, power and speed problem. We will compare our proposed algorithm with previous approach. For image quality measurement we will use some scientific parameters those are PSNR, SSIM, FSIM. Implementation of proposed algorithm will be done by Matlab and hardware implementation will be done by using of Verilog on Xilinx 14.1 simulator. Verification will be done on Model sim.
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To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
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IEEE 2014 DOTNET IMAGE PROCESSING PROJECTS Edge based ivd segmentation system
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Edge-Based IVD Segmentation System
Abstract:-
The determination of flame or fire edges is the process of identifying
a boundary between the area where there is thermo chemical reaction and those
without. It is a precursor to image-based flame monitoring, early fire detection, fire
evaluation, and the determination of flame and fire parameters. Several traditional
edge-detection methods have been tested to identify flame edges, but the results
achieved have been disappointing.Some research works related to flame and fire
edge detection were reported for different applications; however, the methods do
not emphasize the continuity and clarity of the flame and fire edges.A computing
algorithm is thus proposed to define flame and fire edges clearly and continuously.
The algorithm detects the coarse and superfluous edges in a flame/fire image first
and then identifies the edges of the flame/fire and removes the irrelevant artifacts.
The auto adaptive feature of the algorithm ensures that the primary symbolic
flame/fire edges are identified for different scenarios. Experimental results for
different flame images and video frames proved the effectiveness and robustness of
2. the algorithm. Although the system is based on a simple edge detection method
and applied on sagittal and axial planes, it provides fast, memory efficient, and
outstanding segmentation results for both planes, which is unprecedented. This
binary gradient mask has been superimposed Over the original spine image to
obtain the new image that Contains objects less than original image. The most
important element in validating the accuracy of any segmentation algorithm is the
gold standard. Particularly, in the image segmentation problem.
Existing System:-
The thresholds play an important role which used in the image edge
detection. The edge is not only the basic feature of an image but also the
basis of shape quality analysis.
Self-adaptive Threshold Based on Otsu -There are lots of image
segmentation methods based on gray-scale histogram Otsu method was also
used in edge detections to get the high threshold.
In this Technique quality of the image is poor and doesn’t validate the
surroundings.
A new binary threshold image has been created followed by the
determination of the connected components (objects) and determining the
class of each component.
Proposed System:-
A computing algorithm is thus proposed to define flame and fire edges
clearly and continuously.
3. The auto adaptive feature of the algorithm ensures that the primary symbolic
flame/fire edges are identified for different scenarios. Experimental results
for different flame images and video frames proved the effectiveness and
robustness of the algorithm.
It is desirable to develop a dedicated edge detection method for flame and
fire image processing. Accordingly, a new computing algorithm is proposed
in this paper to process a combustion image and to identify flame/fire edges.
By providing experimental results and comparisons, we demonstrate an
algorithm that can achieve a high-quality simplification result.
Hardware Requirements:-
SYSTEM : Pentium IV 2.4 GHz
HARD DISK : 40 GB
RAM : 256 MB
Software Requirements:-
Operating system : Windows XP Professional
IDE : Microsoft Visual Studio .Net 2010
Coding Language : C#.net.