Signal Processing

This project aims at developing android apps for automatic emotion analysis from the voice data. Here we have created a database in Odia language for emotion analysis.

Understanding one’s feelings at the time of communication is constructive in comprehending the conversation and responding appropriately. Currently, this part of human–computer interaction has not yet entirely been solved, and except for a limited number of applications, there is no general solution to this problem.

In recent years in the context of the rapid development of Artificial Intelligence, speech emotion recognition is gradually becoming a challenging research. Human language communication has two modes, written mode and spoken mode. Though linguistic information is the same in both the modes, the latter also carries some paralinguistic information.

The paralinguistic information refers to the speech sounds that carry other speaker related information like, age, sex, emotion and attitude .The most important and complex of them is emotion.

Recognizing emotional content in speech is an indispensable requirement for efficient human-machine interaction.

Human vision is limited to perceive the objects under darkness in presence of highly illuminated light sources. This causes a major problem during night driving by the drivers to watch at darker regions when high beams of vehicle headlights are projected on their eyes.

The same problem arises while capturing information by the traffic management system due to direct projection of street light and vehicle high beam on a CCD camera. Very little research has been carried out to address this problem but no significant results have come out till now.

The existing dark image enhancement algorithms can effectively enhance the darker regions but fail to enhance the brighter regions that are over saturated. This leads to fading of the nearby darker objects resulting in information loss.

Hence, there is a requirement to develop an algorithm which can not only enhance the dark regions of an image but at the same time effectively manipulate the local contrast of the bright regions for proper overall enhancement of an image without any significant loss of original information.

Potholes and speed breakers on road can generate severe damage to tires and vehicles. Especially in India, vehicle collision and accidents happen due to immense depth of potholes on road. Detection and repairing of potholes and speed breakers is a major challenge for Intelligent Transportation System (ITS) service and road management system.

The proposed algorithm not only detects potholes and speed breaker in real-time but also gives an enhanced, highlighted video output for proper recognition of potholes and speed breakers under varieties of circumstances.

The algorithm makes use of a 2-D high pass filter for detecting the outlines of potholes and speed breakers since they represent high frequency. A newly developed horizontal, vertical and diagonal (HVD) filter is developed which enhances the variations in horizontal, vertical and diagonal directions to highlight the details of speed breakers and potholes effectively. Subsequently, the detected region is segmented and filled with colour so that the region will be properly highlighted and visible to the driver in real-time.

Electronics Engineering

Electronics Engineering

Electronics Engineering

Electronics Engineering

Electronics Engineering

Electronics Engineering

Electronics Engineering

Computer Applications

Dept. of Electronics & Instrumentation Engineering, SiliconTech

Dept. of Electronics & Communication Engineering, SiliconTech