Underwater Image Processing using Graphics Processing Unit (GPU)

Image processing is a method used for enhancement of an image or to extract some useful information from the image. It is a type of signal processing in which input is an image and output may be an image or any characteristics/features associated with that image. In this paper we will be focusing on a specific type of Image Processing i.e. Underwater Image Processing. Underwater Image Processing has always faced the problem of imbalance in colour distribution and this problem can be tackled by the simplest algorithm for colour balancing. We will be proceeding with the assumption that the highest values of R, G, B observed in the image corresponds to white and the lowest values corresponds to darkness. The underwater images are majorly saturated by blue colour because of its short wavelength and in this paper, we aim to enhance the image. We proposed a colour balancing algorithm for normalizing the image. The entire process will first be carried out on a CPU followed by a GPU. We will then compare the speedup obtained. Speedup is an important parameter in the field on image processing since a better speedup can help reduce the computation time significantly while maintaining a higher efficiency

Implementation of Bird Species Detection Algorithm using Deep Learning

Automatically identifying what types of the bird is present in the sound recording using the monitor reading. To distinguishing automatic birds based on their sound patterns.This is useful in the field of ornithology for studying bird species and their behavior based on their sound. Proposed method will be used to distinguish birds automatically using different sound processing methods and mechanical learning methods based on their chirping patterns. We propose a sequential model for audio features within a short interval of time. The model will be used Mel Frequency Cepstral Coefficients to extract features from the audio files and presented it in the model. The proposed work classifies the data set containing three species of bird, and outperform support vector machines

Early Stage Detection of Parkinson Disease

Parkinson’s disease is a chronic neurodegenerative condition that demonstrate the progressive loss of the ability to correlate movements mainly occurs in the elderly. For the purpose of monitoring tremors in Parkinson’s disease, a system has to be designed and developed. For coordination of movements, people with Parkinson’s, deprive of a chemical called dopamine which behaves as the messenger between the brain parts and the nervous system .Detecting Parkinson’s disease is a very arduous task as there is no evidence currently present to do this. Therefore, the main intention of our work is the designing of a system for recognizing Parkinson’s disease at an initial stage. An Android application is being designed that allows the status of PD patients to be assessed based on the tests found on the Unified Parkinson’s Disease Rating Scale approved by the Movement Disorders Society (MDS-UPDRS)

Implementation of Airy function using Graphics Processing Unit (GPU)

Special mathematical functions are an integral part of Fractional Calculus, one of them is the Airy function. But it’s a gruelling task for the processor as well as system that is constructed around the function when it comes to evaluating the special mathematical functions on an ordinary Central Processing Unit (CPU). The Parallel processing capabilities of a Graphics processing Unit (GPU) hence is used. In this paper GPU is used to get a speedup in time required, with respect to CPU time for evaluating the Airy function on its real domain. The objective of this paper is to provide a platform for computing the special functions which will accelerate the time required for obtaining the result and thus comparing the performance of numerical solution of Airy function using CPU and GPU