Proposed Hybrid Text and Image Compression Parallel Algorithm

Mar 23, 2021, 1:20 PM
20m
Conf. Room 2 (ASGC)

Conf. Room 2

ASGC

Oral Presentation Data Management & Big Data Data Management & Big Data Session

Speaker

Mr Yash Bitla (Don Bosco Institute of Technology)

Description

Compression is a course used by numerous applications and techniques to make data transfer laidback and swift. Similarly, there are different types of data shared across such as text and image almost every second of our lives. However, with the growing number of working applications and users the compression techniques are limited and yet to explore and deploy. Hence, we tried to come up with a new compression route using LZSS and Huffman Coding for text compression. Also, we plan on incorporating this hybrid text compression using Parallel Processing that can drastically improve the time complexity of our algorithm. Deep convolution neural network is an underestimated and extensive tool for addressing image compression. We have tried to use the above technologies to achieve higher compression ratio than typical compression algorithms available. Also, we have used hybrid CNN to generate a better image which is unlike from existing techniques. Correspondingly including parallelization technique has helped us to optimize the output and reduce the responding time.

Primary author

Prof. Kalpita Ajinkya Wagaskar (Don Bosco Institute of Technology)

Co-author

Mr Yash Bitla (Don Bosco Institute of Technology)

Presentation materials