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Unsupervised Method for Face Photo – Sketch Synthesis and Recognition

Today face recognition is a very important field in biometric identification. Face sketch recognition is one of the special type face recognition. In this paper, presents an unsupervised method for face photo- sketch recognition. The face photo- sketch synthesis has two main steps. One is edge detection for only recognition of face and secondly is for hair detection. In the recognition step, the artist sketch is compared with the generated sketch. PCA and LDA are used to extract features from the sketch images. The k-nearest neighbor classifier with Euclidean distance is used in the classification step. It has a useful application for digital entertainment and law enforcement.

Published by: Seena Jose, Prof. Shivapanchashari

Author: Seena Jose

Paper ID: V3I3-1177

Paper Status: published

Published: May 4, 2017

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A Smart Phone Based Accident Fall Detection, Positioning and Rescue System

This paper proposes the architecture of accident fall detection, positioning and rescue system that uses 3G networks. To perceive the fall detection algorithm, the angles acquired by the electronic compass and the waveform sequence of the tri-axial accelerometer on the smart phone are used as the system inputs. The obtained signals are used to produce an ordered feature sequence and then tested in consecutive way by the proposed cascade classifier for identification purpose. As soon as equivalent characteristic is confirmed by the classifier at the current state, it can continue to the state; contrarily the system will come back to the initial state and halt for the emergence of another feature sequence. When a fall accident event is diagnosed the victim’s position can be acquired by global positioning system (GPS) and forwarded to the rescue centre via 3G network so that immediate medical help can be provided.With the proposed cascaded classification architecture, the computational burden and power consumption issue on the smart phone system can be mollified. Moreover, known fall incident detection accuracy and reliability up to 92% on the sensitivity and 99. 75% on the specificity.

Published by: Keerthana .B, Nikita Pandya, Pooja Joshi, Neha .N, Dr. S. Sathiyan

Author: Keerthana .B

Paper ID: V3I3-1186

Paper Status: published

Published: May 4, 2017

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Traumatic Fibroma of the Upper Lip: Case Report of an Uncommon Presentation

Local reactive focal overgrowth is frequently found in the oral cavities. Different types of localized reactive lesions may occur on the gingiva, including focal fibrous hyperplasia, pyogenic granuloma, peripheral giant cell granuloma and peripheral ossifying fibroma (POF). The inflammatory hyperplastic lesion may be defined as “an increase in the size of an organ or tissue due to an increase in the number of constituent cells, as a local response of tissue to injury. Irritation fibroma clinically resembles as pyogenic granuloma, peripheral giant cell granuloma or odontogenic tumors, so radiographic and histopathological examination is essential for accurate diagnosis.

Published by: Dr. Monica

Author: Dr. Monica

Paper ID: V3I3-1165

Paper Status: published

Published: May 4, 2017

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Automatic Diagnosis of Epilepsy Using Electroencephalogram (EEG) Signal Analysis

Epilepsy is a very common neurological disorder. Electroencephalogram (EEG) is the major diagnostic tool used for analyzing the human epileptic seizure activity and there is a strong need of an efficient automatic seizure detection using it to ease the diagnosis. This work aims at an automatic system for diagnosis of epilepsy. Here we extract some features like fractal dimensions, sample entropy, Lyapunov exponent, etc of both normal and epileptic EEG signals. These feature values are used as inputs to train classifiers like Artificial neural networks, support vector machines, probabilistic neural networks etc., After the training, we test the classifier with test EEG data.

Published by: M. V Satya Sai Chandra, Dr. Paul K Joseph, Dr. Thasneem Fathima

Author: M. V Satya Sai Chandra

Paper ID: V3I3-1180

Paper Status: published

Published: May 4, 2017

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Indoor Localisation Using RSSI Technique

As positioning systems that can track and monitor moving objects/people become more widely used in our everyday life, we face the challenge of doing the same in places where such systems cannot be practically implemented. This is where the need for an alternate system arises. The main objective of the project is to provide a wireless means of tracking and monitoring objects/people in closed environments such as mines. There are two parts in this system- Transmitter which is a small portable device that can be carried around by the user inside the mines, and Receiver which is stationary, can be interfaced to a PC or remotely connected to PCs outside the mine through Internet of Things. Additionally, a climatology unit is kept at various points in the mines, to monitor the ambient parameters such as temperature, humidity, light intensity levels along with a safety sensor that detects vibrations caused by landslides or earthquakes. The receiver display shows the location of the moving object/person and the values of the ambient parameters. The tracking and monitoring is done by using RSSI algorithm, that is implemented using Visual Basic software.

Published by: Ramya .B, Saranya .N, Jyotsna .M, Hardhika Mahavir, Senthil Kumar

Author: Ramya .B

Paper ID: V3I3-1178

Paper Status: published

Published: May 4, 2017

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Advanced Foot Step Power Generation Using Piezo-Electric Sensors

Day by day, the population of the country in-creased and the requirement of the power is also increased. At the same time the wastage of energy also increased in many ways. So reforming this energy back to usable form is the major concern. As technology is developed and the use of gadgets, electronic devices also increased. Power generation using conservative methods becoming deficient. There is a need arises for a different power generation method. At the same time the energy is wasted due to human locomotion. To overcome this problem, the energy wastage is converted to usable form using the piezoelectric sensor. This sensor converts the pressure on it to a voltage. By using this energy saving method, footstep power generation system we are generating power.

Published by: Anirudha Chavan, Shyam Lakhadive, Vaibhav Pondhe, Prof. Vineeta Philip

Author: Anirudha Chavan

Paper ID: V3I3-1172

Paper Status: published

Published: May 4, 2017

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