Lizy Abraham | University of Kerala (original) (raw)

Papers by Lizy Abraham

Research paper thumbnail of A Review on Early Diagnosis of Lung Cancer from CT Images Using Deep Learning

Algorithms for intelligent systems, 2023

Research paper thumbnail of Hybrid Transfer Learning Approach using Multiple Pre-trained Models for Classification of Outdoor Images into AQI Classes

2022 IEEE 7th International Conference on Recent Advances and Innovations in Engineering (ICRAIE)

Research paper thumbnail of Towards Resource-aware DNN Partitioning for Edge Devices with Heterogeneous Resources

GLOBECOM 2022 - 2022 IEEE Global Communications Conference

Research paper thumbnail of Edge-AI Implementation for Milk Adulteration Detection

2022 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)

Research paper thumbnail of Complexity-Driven CNN Compression for Resource-constrained Edge AI

Cornell University - arXiv, Aug 26, 2022

Recent advances in Artificial Intelligence (AI) on the Internet of Things (IoT)-enabled network e... more Recent advances in Artificial Intelligence (AI) on the Internet of Things (IoT)-enabled network edge has realized edge intelligence in several applications such as smart agriculture, smart hospitals, and smart factories by enabling low-latency and computational efficiency. However, deploying state-of-theart Convolutional Neural Networks (CNNs) such as VGG-16 and ResNets on resource-constrained edge devices is practically infeasible due to their large number of parameters and floating-point operations (FLOPs). Thus, the concept of network pruning as a type of model compression is gaining attention for accelerating CNNs on low-power devices. State-of-the-art pruning approaches, either structured or unstructured do not consider the different underlying nature of complexities being exhibited by convolutional layers and follow a training-pruningretraining pipeline, which results in additional computational overhead. In this work, we propose a novel and computationally efficient pruning pipeline by exploiting the inherent layer-level complexities of CNNs. Unlike typical methods, our proposed complexity-driven algorithm selects a particular layer for filterpruning based on its contribution to overall network complexity. We follow a procedure that directly trains the pruned model and avoids the computationally complex ranking and fine-tuning steps. Moreover, we define three modes of pruning, namely parameter-aware (PA), FLOPs-aware (FA), and memory-aware (MA), to introduce versatile compression of CNNs. Our results show the competitive performance of our approach in terms of accuracy and acceleration. Lastly, we present a trade-off between different resources and accuracy which can be helpful for developers in making the right decisions in resource-constrained IoT environments.

Research paper thumbnail of Copy-move Image Forgery Localization Using Deep Feature Pyramidal Network

2021 International Conference on Advances in Computing and Communications (ICACC)

Fake news, frequently making use of tampered photos, has currently emerged as a global epidemic, ... more Fake news, frequently making use of tampered photos, has currently emerged as a global epidemic, mainly due to the widespread use of social media as a present alternative to traditional news outlets. This development is often due to the swiftly declining price of advanced cameras and phones, which prompts the simple making of computerized pictures. The accessibility and usability of picture-altering softwares make picture-altering or controlling processes significantly simple, regardless of whether it is for the blameless or malicious plan. Various investigations have been utilized around to distinguish this sort of controlled media to deal with this issue. This paper proposes an efficient technique of copy-move forgery detection using the deep learning method. Two deep learning models such as Buster Net and VGG with FPN are used here to detect copy move forgery in digital images. The two models' performance is evaluated using the CoMoFoD dataset. The experimental result shows that VGG with FPN outperforms the Buster Net model for detecting forgery in images with an accuracy of 99.8% whereas the accuracy for the Buster Net model is 96.9%.

Research paper thumbnail of Study and Analysis of Satellite Images for the Extraction of Structural Features

Research paper thumbnail of An Ensemble Deep Learning Model for Forecasting Hourly PM2.5 Concentrations

Research paper thumbnail of Target Tracking

Research paper thumbnail of Analysis of Different Temperature Sensors for Space Applications

In this paper, a temperature measurement using DS18B20 is implemented which is an economic and fe... more In this paper, a temperature measurement using DS18B20 is implemented which is an economic and feasible method. This study mainly deals with the applicability of DS18B20 and other sensors in space applications. Temperature is an important parameter to monitor. The total process consists of sensing of the temperature using RTD, Thermocouple, LM35, DS18B20 , PIC16F877A and sent to PC using RS232 serial interface, display in the way of digital and waveform using a real time software Lab VIEW (Laboratory Virtual Instrumentation Engineering Workbench) of National Instruments, USA and comparing with conventional sensor used in industry.

Research paper thumbnail of Point tracking with lensless smart sensors

2017 IEEE SENSORS, 2017

This paper presents the applicability of a novel Lensless Smart Sensor (LSS) developed by Rambus,... more This paper presents the applicability of a novel Lensless Smart Sensor (LSS) developed by Rambus, Inc. in 3D positioning and tracking. The unique diffraction pattern attached to the sensor enables more precise position tracking than possible with lenses by capturing more information about the scene. In this work, the sensor characteristics is assessed and accuracy analysis is accomplished for the single point tracking scenario.

Research paper thumbnail of Vehicle Detection and Classification from High Resolution Aerial Views using Morphological Operations

International Journal of Engineering Research and, 2015

In the past decades satellite imagery has been used successfully for weather forecasting, geograp... more In the past decades satellite imagery has been used successfully for weather forecasting, geographical and geological applications. Low resolution satellite images are sufficient for these sorts of applications. But the technological developments in the field of satellite imaging provide high resolution sensors which expands its field of application. Thus the High Resolution Satellite Imagery (HRSI) proved to be a suitable alternative to aerial photogrammetric data to provide a new data source for object detection. Since the traffic rates in developing countries are enormously increasing, vehicle detection from satellite data will be a better choice for automating such systems. In this work, a novel technique for vehicle detection from the images obtained from high resolution sensors is proposed. Though we are using high resolution images, vehicles are seen only as tiny spots, difficult to distinguish from the background. But we are able to obtain a detection rate not less than 0.9. Thereafter we classify the detected vehicles into cars and trucks and find the count of them.

Research paper thumbnail of Boost converter based power factor correction for single phase rectifier using fuzzy logic control

2014 First International Conference on Computational Systems and Communications (ICCSC), 2014

Power Factor which is the ratio between the real or actual power and the apparent power is a very... more Power Factor which is the ratio between the real or actual power and the apparent power is a very essential parameter in power system. It indicates how effectively the real power of the system has been utilized. In any electrical power system, a load with a low power factor draws more current than a high power factor load, for the same amount of useful power transferred. The most popular topology in Power Factor Correction (PFC) applications is certainly the boost topology. The boost topology is very simple and allows low-distorted input currents and almost unity power factor with different control techniques. A new fuzzy logic control strategy in a boost converter based PFC method for single phase rectifier is presented in this work. The proposed fuzzy logic control system has two inputs and one output. The proposed PFC control is based on boost converter operating at continuous conduction mode and provides a higher switching frequency.

Research paper thumbnail of An efficient shadow detection method for high resolution satellite images

2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12), 2012

The problem of shadowing is particularly significant in high-resolution satellite imaging (HRSI) ... more The problem of shadowing is particularly significant in high-resolution satellite imaging (HRSI) which causes either a reduction or total loss of information in the image. The research on segmenting shadow regions is of great significance for image interpretation and it is a supportive tool to detect manmade structures. This paper proposes a solution to the problem of automatic extraction of shadow features in color satellite images with high spatial resolution. The algorithm separates shadow from non-shadow by considering the spatial properties of the segmented regions. Experiments are executed on high resolution satellite images, and the results confirm the validity of the proposed method.

Research paper thumbnail of LabVIEW based modelling and analysis of temperature sensors

2014 First International Conference on Computational Systems and Communications (ICCSC), 2014

In this paper, a temperature measurement module using DS18B20 digital temperature sensor is devel... more In this paper, a temperature measurement module using DS18B20 digital temperature sensor is developed to work as a standalone system. The module is compared with other conventional temperature sensors used in space applications. The total process consists of comparing the temperature obtained using DS18B20 module in real time with RTD, Thermocouple and LM35. PIC16F877A microcontroller is used to read the data from the sensor and send to PC. Lab VIEW (Laboratory Virtual Instrumentation Engineering Workbench) of National Instruments, running on the computer will extract and display the data from the serial port at real time. Finally, using BeagleBoard which is a low-power open-source single-board computer produced by Texas Instruments, the temperature is remotely monitored.

Research paper thumbnail of Analysis of MEMS gyro sensors ADXRS 450 and ADXRS 649 using LabVIEW

2014 First International Conference on Computational Systems and Communications (ICCSC), 2014

Gyroscopes are used for maintaining orientation or measuring the angle of rotation or the rate of... more Gyroscopes are used for maintaining orientation or measuring the angle of rotation or the rate of change of angular rotation. This paper compares angular rate measurement between MEMS digital (ADXRS 450) and analog (ADXRS 649) gyroscope. PIC 18F6520 is used to read the extracted angular rate from ADXRS 450. Digital output extracted from the sensor is error free even in noisy condition. Angular rate output from analog gyro can be read directly without the help of microcontroller but obtained output requires amplification. Difference amplifier AD8202 is used here for the amplification purpose. LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) software running on the computer will extract and display the data from the serial port at real time.

Research paper thumbnail of Analysis of vibration and acoustic sensors for machine health monitoring and its wireless implementation for low cost space applications

2014 First International Conference on Computational Systems and Communications (ICCSC), 2014

Vibrations produced by machinery are vital indicators of machine health. Vibration analysis is us... more Vibrations produced by machinery are vital indicators of machine health. Vibration analysis is used as a tool to determine a machine's condition and the specific cause and location of problems, expediting repairs and minimizing costs. Machinery monitoring programs record a machine's vibration history. Monitoring vibration levels over time allows prediction of problems before serious damage can occur. Acoustic signal and vibration are correlated as pressure variations due to vibration create acoustic signals. The current trend of spacecraft design is to use complex and lightweight space structures to achieve increased functionality at a reduced launch cost. The goal of this research is to analyse output signals from suitable MEMS vibration as well as acoustic sensor ICs and to compare them with piezoelectric sensors. The study also aims in wireless monitoring of vibration as well as acoustic signals from rotating mechanical structures. MEMS sensors are low cost high resolution sensors with promising applications in low cost space applications such as Sounding rockets, Nano satellites and other terrestrial applications.

Research paper thumbnail of A fuzzy based road network extraction from degraded satellite images

2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2013

Satellite imaging sensors like SPOT, IKONOS and GEOEYE provide high resolution images, but the co... more Satellite imaging sensors like SPOT, IKONOS and GEOEYE provide high resolution images, but the cost and complexity is high. If efficient algorithms exist for structural feature extraction like roads, buildings and bridges from satellite images, we can still use low resolution images to a certain extend. Many cases both low and high resolution images are affected by blurring and noisy effects, which seriously affects the feature extraction process. This paper provides an efficient algorithm for road network extraction from satellite images irrespective of their resolution, blurred and noisy effects.

Research paper thumbnail of Cloud Extraction and Removal in Aerial and Satellite Images

Advances in Intelligent Systems and Computing, 2013

Aerial and satellite images are projected images where clouds and cloud-shadows cause interferenc... more Aerial and satellite images are projected images where clouds and cloud-shadows cause interferences in them. Detecting the presence of clouds over a region is important to isolate cloud-free pixels used to retrieve atmospheric thermodynamic information and surface geophysical parameters. This paper describes an adaptive algorithm to reduce both effects of clouds and their shadows from remote sensed images. The proposed method is implemented and tested with remote sensed RGB and monochrome images and also for visible (VIS) satellite imagery and infrared (IR) imagery. The results show that this approach is effective in extracting infected pixels and their compensation.

Research paper thumbnail of A Fuzzy Based Automatic Bridge Detection Technique for Satellite Images

Communications in Computer and Information Science, 2012

Automatic detection of artificial objects from satellite images are important source of informati... more Automatic detection of artificial objects from satellite images are important source of information in many applications such as terrain mapping by remote sensing and GIS (Geographic Information System) applications. In this paper, a fuzzy based integrated algorithm for automatic detection of bridges over water is proposed. In the first step, the multispectral satellite image is given to a fuzzy based thresholding method to segment water regions from the background. Then candidate bridge pixels are extracted according to area analysis and bridge extraction algorithm developed. The algorithm is formulated in such a way that, the method can be applied to any complexity levels and any spatial resolutions. The approach in this paper has been implemented and tested with different types of satellite images to validate the superior performance of the algorithm.

Research paper thumbnail of A Review on Early Diagnosis of Lung Cancer from CT Images Using Deep Learning

Algorithms for intelligent systems, 2023

Research paper thumbnail of Hybrid Transfer Learning Approach using Multiple Pre-trained Models for Classification of Outdoor Images into AQI Classes

2022 IEEE 7th International Conference on Recent Advances and Innovations in Engineering (ICRAIE)

Research paper thumbnail of Towards Resource-aware DNN Partitioning for Edge Devices with Heterogeneous Resources

GLOBECOM 2022 - 2022 IEEE Global Communications Conference

Research paper thumbnail of Edge-AI Implementation for Milk Adulteration Detection

2022 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)

Research paper thumbnail of Complexity-Driven CNN Compression for Resource-constrained Edge AI

Cornell University - arXiv, Aug 26, 2022

Recent advances in Artificial Intelligence (AI) on the Internet of Things (IoT)-enabled network e... more Recent advances in Artificial Intelligence (AI) on the Internet of Things (IoT)-enabled network edge has realized edge intelligence in several applications such as smart agriculture, smart hospitals, and smart factories by enabling low-latency and computational efficiency. However, deploying state-of-theart Convolutional Neural Networks (CNNs) such as VGG-16 and ResNets on resource-constrained edge devices is practically infeasible due to their large number of parameters and floating-point operations (FLOPs). Thus, the concept of network pruning as a type of model compression is gaining attention for accelerating CNNs on low-power devices. State-of-the-art pruning approaches, either structured or unstructured do not consider the different underlying nature of complexities being exhibited by convolutional layers and follow a training-pruningretraining pipeline, which results in additional computational overhead. In this work, we propose a novel and computationally efficient pruning pipeline by exploiting the inherent layer-level complexities of CNNs. Unlike typical methods, our proposed complexity-driven algorithm selects a particular layer for filterpruning based on its contribution to overall network complexity. We follow a procedure that directly trains the pruned model and avoids the computationally complex ranking and fine-tuning steps. Moreover, we define three modes of pruning, namely parameter-aware (PA), FLOPs-aware (FA), and memory-aware (MA), to introduce versatile compression of CNNs. Our results show the competitive performance of our approach in terms of accuracy and acceleration. Lastly, we present a trade-off between different resources and accuracy which can be helpful for developers in making the right decisions in resource-constrained IoT environments.

Research paper thumbnail of Copy-move Image Forgery Localization Using Deep Feature Pyramidal Network

2021 International Conference on Advances in Computing and Communications (ICACC)

Fake news, frequently making use of tampered photos, has currently emerged as a global epidemic, ... more Fake news, frequently making use of tampered photos, has currently emerged as a global epidemic, mainly due to the widespread use of social media as a present alternative to traditional news outlets. This development is often due to the swiftly declining price of advanced cameras and phones, which prompts the simple making of computerized pictures. The accessibility and usability of picture-altering softwares make picture-altering or controlling processes significantly simple, regardless of whether it is for the blameless or malicious plan. Various investigations have been utilized around to distinguish this sort of controlled media to deal with this issue. This paper proposes an efficient technique of copy-move forgery detection using the deep learning method. Two deep learning models such as Buster Net and VGG with FPN are used here to detect copy move forgery in digital images. The two models' performance is evaluated using the CoMoFoD dataset. The experimental result shows that VGG with FPN outperforms the Buster Net model for detecting forgery in images with an accuracy of 99.8% whereas the accuracy for the Buster Net model is 96.9%.

Research paper thumbnail of Study and Analysis of Satellite Images for the Extraction of Structural Features

Research paper thumbnail of An Ensemble Deep Learning Model for Forecasting Hourly PM2.5 Concentrations

Research paper thumbnail of Target Tracking

Research paper thumbnail of Analysis of Different Temperature Sensors for Space Applications

In this paper, a temperature measurement using DS18B20 is implemented which is an economic and fe... more In this paper, a temperature measurement using DS18B20 is implemented which is an economic and feasible method. This study mainly deals with the applicability of DS18B20 and other sensors in space applications. Temperature is an important parameter to monitor. The total process consists of sensing of the temperature using RTD, Thermocouple, LM35, DS18B20 , PIC16F877A and sent to PC using RS232 serial interface, display in the way of digital and waveform using a real time software Lab VIEW (Laboratory Virtual Instrumentation Engineering Workbench) of National Instruments, USA and comparing with conventional sensor used in industry.

Research paper thumbnail of Point tracking with lensless smart sensors

2017 IEEE SENSORS, 2017

This paper presents the applicability of a novel Lensless Smart Sensor (LSS) developed by Rambus,... more This paper presents the applicability of a novel Lensless Smart Sensor (LSS) developed by Rambus, Inc. in 3D positioning and tracking. The unique diffraction pattern attached to the sensor enables more precise position tracking than possible with lenses by capturing more information about the scene. In this work, the sensor characteristics is assessed and accuracy analysis is accomplished for the single point tracking scenario.

Research paper thumbnail of Vehicle Detection and Classification from High Resolution Aerial Views using Morphological Operations

International Journal of Engineering Research and, 2015

In the past decades satellite imagery has been used successfully for weather forecasting, geograp... more In the past decades satellite imagery has been used successfully for weather forecasting, geographical and geological applications. Low resolution satellite images are sufficient for these sorts of applications. But the technological developments in the field of satellite imaging provide high resolution sensors which expands its field of application. Thus the High Resolution Satellite Imagery (HRSI) proved to be a suitable alternative to aerial photogrammetric data to provide a new data source for object detection. Since the traffic rates in developing countries are enormously increasing, vehicle detection from satellite data will be a better choice for automating such systems. In this work, a novel technique for vehicle detection from the images obtained from high resolution sensors is proposed. Though we are using high resolution images, vehicles are seen only as tiny spots, difficult to distinguish from the background. But we are able to obtain a detection rate not less than 0.9. Thereafter we classify the detected vehicles into cars and trucks and find the count of them.

Research paper thumbnail of Boost converter based power factor correction for single phase rectifier using fuzzy logic control

2014 First International Conference on Computational Systems and Communications (ICCSC), 2014

Power Factor which is the ratio between the real or actual power and the apparent power is a very... more Power Factor which is the ratio between the real or actual power and the apparent power is a very essential parameter in power system. It indicates how effectively the real power of the system has been utilized. In any electrical power system, a load with a low power factor draws more current than a high power factor load, for the same amount of useful power transferred. The most popular topology in Power Factor Correction (PFC) applications is certainly the boost topology. The boost topology is very simple and allows low-distorted input currents and almost unity power factor with different control techniques. A new fuzzy logic control strategy in a boost converter based PFC method for single phase rectifier is presented in this work. The proposed fuzzy logic control system has two inputs and one output. The proposed PFC control is based on boost converter operating at continuous conduction mode and provides a higher switching frequency.

Research paper thumbnail of An efficient shadow detection method for high resolution satellite images

2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12), 2012

The problem of shadowing is particularly significant in high-resolution satellite imaging (HRSI) ... more The problem of shadowing is particularly significant in high-resolution satellite imaging (HRSI) which causes either a reduction or total loss of information in the image. The research on segmenting shadow regions is of great significance for image interpretation and it is a supportive tool to detect manmade structures. This paper proposes a solution to the problem of automatic extraction of shadow features in color satellite images with high spatial resolution. The algorithm separates shadow from non-shadow by considering the spatial properties of the segmented regions. Experiments are executed on high resolution satellite images, and the results confirm the validity of the proposed method.

Research paper thumbnail of LabVIEW based modelling and analysis of temperature sensors

2014 First International Conference on Computational Systems and Communications (ICCSC), 2014

In this paper, a temperature measurement module using DS18B20 digital temperature sensor is devel... more In this paper, a temperature measurement module using DS18B20 digital temperature sensor is developed to work as a standalone system. The module is compared with other conventional temperature sensors used in space applications. The total process consists of comparing the temperature obtained using DS18B20 module in real time with RTD, Thermocouple and LM35. PIC16F877A microcontroller is used to read the data from the sensor and send to PC. Lab VIEW (Laboratory Virtual Instrumentation Engineering Workbench) of National Instruments, running on the computer will extract and display the data from the serial port at real time. Finally, using BeagleBoard which is a low-power open-source single-board computer produced by Texas Instruments, the temperature is remotely monitored.

Research paper thumbnail of Analysis of MEMS gyro sensors ADXRS 450 and ADXRS 649 using LabVIEW

2014 First International Conference on Computational Systems and Communications (ICCSC), 2014

Gyroscopes are used for maintaining orientation or measuring the angle of rotation or the rate of... more Gyroscopes are used for maintaining orientation or measuring the angle of rotation or the rate of change of angular rotation. This paper compares angular rate measurement between MEMS digital (ADXRS 450) and analog (ADXRS 649) gyroscope. PIC 18F6520 is used to read the extracted angular rate from ADXRS 450. Digital output extracted from the sensor is error free even in noisy condition. Angular rate output from analog gyro can be read directly without the help of microcontroller but obtained output requires amplification. Difference amplifier AD8202 is used here for the amplification purpose. LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) software running on the computer will extract and display the data from the serial port at real time.

Research paper thumbnail of Analysis of vibration and acoustic sensors for machine health monitoring and its wireless implementation for low cost space applications

2014 First International Conference on Computational Systems and Communications (ICCSC), 2014

Vibrations produced by machinery are vital indicators of machine health. Vibration analysis is us... more Vibrations produced by machinery are vital indicators of machine health. Vibration analysis is used as a tool to determine a machine's condition and the specific cause and location of problems, expediting repairs and minimizing costs. Machinery monitoring programs record a machine's vibration history. Monitoring vibration levels over time allows prediction of problems before serious damage can occur. Acoustic signal and vibration are correlated as pressure variations due to vibration create acoustic signals. The current trend of spacecraft design is to use complex and lightweight space structures to achieve increased functionality at a reduced launch cost. The goal of this research is to analyse output signals from suitable MEMS vibration as well as acoustic sensor ICs and to compare them with piezoelectric sensors. The study also aims in wireless monitoring of vibration as well as acoustic signals from rotating mechanical structures. MEMS sensors are low cost high resolution sensors with promising applications in low cost space applications such as Sounding rockets, Nano satellites and other terrestrial applications.

Research paper thumbnail of A fuzzy based road network extraction from degraded satellite images

2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2013

Satellite imaging sensors like SPOT, IKONOS and GEOEYE provide high resolution images, but the co... more Satellite imaging sensors like SPOT, IKONOS and GEOEYE provide high resolution images, but the cost and complexity is high. If efficient algorithms exist for structural feature extraction like roads, buildings and bridges from satellite images, we can still use low resolution images to a certain extend. Many cases both low and high resolution images are affected by blurring and noisy effects, which seriously affects the feature extraction process. This paper provides an efficient algorithm for road network extraction from satellite images irrespective of their resolution, blurred and noisy effects.

Research paper thumbnail of Cloud Extraction and Removal in Aerial and Satellite Images

Advances in Intelligent Systems and Computing, 2013

Aerial and satellite images are projected images where clouds and cloud-shadows cause interferenc... more Aerial and satellite images are projected images where clouds and cloud-shadows cause interferences in them. Detecting the presence of clouds over a region is important to isolate cloud-free pixels used to retrieve atmospheric thermodynamic information and surface geophysical parameters. This paper describes an adaptive algorithm to reduce both effects of clouds and their shadows from remote sensed images. The proposed method is implemented and tested with remote sensed RGB and monochrome images and also for visible (VIS) satellite imagery and infrared (IR) imagery. The results show that this approach is effective in extracting infected pixels and their compensation.

Research paper thumbnail of A Fuzzy Based Automatic Bridge Detection Technique for Satellite Images

Communications in Computer and Information Science, 2012

Automatic detection of artificial objects from satellite images are important source of informati... more Automatic detection of artificial objects from satellite images are important source of information in many applications such as terrain mapping by remote sensing and GIS (Geographic Information System) applications. In this paper, a fuzzy based integrated algorithm for automatic detection of bridges over water is proposed. In the first step, the multispectral satellite image is given to a fuzzy based thresholding method to segment water regions from the background. Then candidate bridge pixels are extracted according to area analysis and bridge extraction algorithm developed. The algorithm is formulated in such a way that, the method can be applied to any complexity levels and any spatial resolutions. The approach in this paper has been implemented and tested with different types of satellite images to validate the superior performance of the algorithm.