Ramya Rangasamy | KSR COLLEGE OF TECHNOLOGY,(ANNA UNIVERSITY, COIMBATORE) (original) (raw)
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Papers by Ramya Rangasamy
Graph cut image partitioning is used to segment any type of the image data. The image data is tra... more Graph cut image partitioning is used to segment any type of the image data. The image data is transformed by a kernel function so that the piecewise constant model of the graph cut formulation becomes applicable. The method affords an effective alternative to complex modeling of the original image data while taking advantage of the computational benefits of graph cuts.
2020 International Conference on Computer Communication and Informatics (ICCCI), 2020
Fruit disease detection is vital at early stage since it will affect the agricultural field. In t... more Fruit disease detection is vital at early stage since it will affect the agricultural field. In this paper, mainly consider the detection and analysis of fruit infections which is available in the plant areas and storage of data about the agricultural filed and details of farmers in database and recovering the data using Cloud computing. There are more fruit diseases which occur due to the surrounding conditions, mineral levels, insects in the farm area and other factors. The detected data from the plant area is determined by image processing and stored in the database.
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Multiregion graph cut image partitioning via kernel mapping is used to segment any type of the im... more Multiregion graph cut image partitioning via kernel mapping is used to segment any type of the image data.The piecewise constant model of the graph cut formulation becomes applicable when the image data is transformed by a kernel function. The objective function contains an original data term to evaluate the deviation of the transformed data within each segmentation region, from the piecewise constant model, and a smoothness boundary preserving regularization term. Using a common kernel function, energy minimization typically consists of iterating image partitioning by graph cut iterations and evaluations of region parameters via fixed point computation.The method results in good segmentations and runs faster the graph cut methods. The segmentation from MRI data is an important but time consuming task performed manually by medical ex- perts. The segmentation of MRI image is challenging due to the high diversity in appearance of tissue among thepatient.A semi-automatic interactive brain segmentation system with the ability to adjust operator control is achieved in this method.
Multiregion graph cut image partitioning via kernel mapping is used to segment any type of the im... more Multiregion graph cut image partitioning via kernel mapping is used to segment any type of the image data. The image data is transformed by a kernel function so that the piecewise constant model of the graph cut formulation becomes applicable. The objective function contains an original data term to evaluate the deviation of the transformed data within each segmentation region, from the piecewise constant model, and a smoothness boundary preserving regularization term. The method affords an effective alternative to complex modeling of the original image data while taking advantage of the computational benefits of graph cuts. Using a common kernel function, energy minimization typically consists of iterating image partitioning by graph cut iterations and evaluations of region parameters via fixed point computation. The method results in good segmentations and runs faster the graph cut methods. The segmentation from MRI data is an important but time consuming task performed manually b...
2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015], 2015
In order to ensure the safe supply of the drinking water the quality needs to be monitor in real ... more In order to ensure the safe supply of the drinking water the quality needs to be monitor in real time. In this paper we present a design and development of a low cost system for real time monitoring of the water quality in IOT(internet of things).the system consist of several sensors is used to measuring physical and chemical parameters of the water. The parameters such as temperature, PH, turbidity, conductivity, dissolved oxygen of the water can be measured. The measured values from the sensors can be processed by the core controller. The raspberry PI B+ model can be used as a core controller. Finally, the sensor data can be viewed on internet using cloud computing.
2014 International Conference on Electronics and Communication Systems (ICECS), 2014
A novel asynchronous S-Box design for AES cryptosystems is proposed and validated. The S-Box is c... more A novel asynchronous S-Box design for AES cryptosystems is proposed and validated. The S-Box is considered as the most critical component in AES crypto-circuits since it consumes the most power and leaks the most information against side channel attacks. The proposed design completely based on a delay insensitive logic paradigm known as Null Conversion Logic (NCL). Asynchronous S-Box is based on self-time logic referred to as NCL which supports few beneficial properties for resisting SCAs such as clock free, duail rail encoding and monotonic transitions so that it consumes less power therefore suitable for energy constrained mobile crypto-applications. These beneficial properties make it difficult for an attacker to decipher secret key embedded within the cryptographic circuits of the FPGA board. Resistant to SCAs of both existing and proposed S-Box design are presented using differential power analysis (DPA) and correlation power analysis (CPA) attacks. The power measurement result showed that the NCL S-Box had lower total power consumption than original and effective against DPA and CPA attacks.
inproceedings by Ramya Rangasamy
Graph cut image partitioning is used to segment any type of the image data. The image data is tra... more Graph cut image partitioning is used to segment any type of the image data. The image data is transformed by a kernel function so that the piecewise constant model of the graph cut formulation becomes applicable. The method affords an effective alternative to complex modeling of the original image data while taking advantage of the computational benefits of graph cuts.
2020 International Conference on Computer Communication and Informatics (ICCCI), 2020
Fruit disease detection is vital at early stage since it will affect the agricultural field. In t... more Fruit disease detection is vital at early stage since it will affect the agricultural field. In this paper, mainly consider the detection and analysis of fruit infections which is available in the plant areas and storage of data about the agricultural filed and details of farmers in database and recovering the data using Cloud computing. There are more fruit diseases which occur due to the surrounding conditions, mineral levels, insects in the farm area and other factors. The detected data from the plant area is determined by image processing and stored in the database.
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Multiregion graph cut image partitioning via kernel mapping is used to segment any type of the im... more Multiregion graph cut image partitioning via kernel mapping is used to segment any type of the image data.The piecewise constant model of the graph cut formulation becomes applicable when the image data is transformed by a kernel function. The objective function contains an original data term to evaluate the deviation of the transformed data within each segmentation region, from the piecewise constant model, and a smoothness boundary preserving regularization term. Using a common kernel function, energy minimization typically consists of iterating image partitioning by graph cut iterations and evaluations of region parameters via fixed point computation.The method results in good segmentations and runs faster the graph cut methods. The segmentation from MRI data is an important but time consuming task performed manually by medical ex- perts. The segmentation of MRI image is challenging due to the high diversity in appearance of tissue among thepatient.A semi-automatic interactive brain segmentation system with the ability to adjust operator control is achieved in this method.
Multiregion graph cut image partitioning via kernel mapping is used to segment any type of the im... more Multiregion graph cut image partitioning via kernel mapping is used to segment any type of the image data. The image data is transformed by a kernel function so that the piecewise constant model of the graph cut formulation becomes applicable. The objective function contains an original data term to evaluate the deviation of the transformed data within each segmentation region, from the piecewise constant model, and a smoothness boundary preserving regularization term. The method affords an effective alternative to complex modeling of the original image data while taking advantage of the computational benefits of graph cuts. Using a common kernel function, energy minimization typically consists of iterating image partitioning by graph cut iterations and evaluations of region parameters via fixed point computation. The method results in good segmentations and runs faster the graph cut methods. The segmentation from MRI data is an important but time consuming task performed manually b...
2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015], 2015
In order to ensure the safe supply of the drinking water the quality needs to be monitor in real ... more In order to ensure the safe supply of the drinking water the quality needs to be monitor in real time. In this paper we present a design and development of a low cost system for real time monitoring of the water quality in IOT(internet of things).the system consist of several sensors is used to measuring physical and chemical parameters of the water. The parameters such as temperature, PH, turbidity, conductivity, dissolved oxygen of the water can be measured. The measured values from the sensors can be processed by the core controller. The raspberry PI B+ model can be used as a core controller. Finally, the sensor data can be viewed on internet using cloud computing.
2014 International Conference on Electronics and Communication Systems (ICECS), 2014
A novel asynchronous S-Box design for AES cryptosystems is proposed and validated. The S-Box is c... more A novel asynchronous S-Box design for AES cryptosystems is proposed and validated. The S-Box is considered as the most critical component in AES crypto-circuits since it consumes the most power and leaks the most information against side channel attacks. The proposed design completely based on a delay insensitive logic paradigm known as Null Conversion Logic (NCL). Asynchronous S-Box is based on self-time logic referred to as NCL which supports few beneficial properties for resisting SCAs such as clock free, duail rail encoding and monotonic transitions so that it consumes less power therefore suitable for energy constrained mobile crypto-applications. These beneficial properties make it difficult for an attacker to decipher secret key embedded within the cryptographic circuits of the FPGA board. Resistant to SCAs of both existing and proposed S-Box design are presented using differential power analysis (DPA) and correlation power analysis (CPA) attacks. The power measurement result showed that the NCL S-Box had lower total power consumption than original and effective against DPA and CPA attacks.