Dual-Compression Based Model Using the Active Object Detection Model
Journal Title: International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR) - Year 2017, Vol 7, Issue 4
Abstract
The major objective of this image compression model is to retain the maximum quality of the main object in focus in the given image. Methods/Statistical analysis: The efficient object detection and localization algorithm has been implemented under this research, for the demarcation of the image zone containing the valuable information. The remaining image contents are compressed with the higher compression ratio based model, and the demarked zone will be compressed with maximum quality preservation method. Findings: The major results are collected in the form of image quality parameters (PSNR, MSE) and compression quality parameters (Compression Ratio) are the taken as the major performance measures. Application/Improvements: The proposed model has been primarily improved for the purpose of image quality improvement under the video conferencing models.
Authors and Affiliations
Hardeep Kaur, Damanpreet Kaur
EVOLUTION OF NEW EFFICIENT LOAD BALANCER ALGORITHM FOR LARGE DATA SETS
Cloud computing is a vital part of this new era IT world or we can say that it is a technology of new age which are used to connect data and application from anywhere around the planet through the internet. Anything and...
Mining Rating of University Performance in Academic Programs and Services
Measuring service quality is a marketing trend that is gradually proving its worth in academic institutions. This study contributes to the growing body of knowledge on service quality measures in higher education (Aldrid...
Insight of Various Pos Tagging Techniques for Hindi Language
Natural language processing (NLP), is the process of extracting meaningful information from natural language. Part of speech (POS) tagging is considered as one of the important tools, for Natural language processing. Par...
An Application of Artificial Intelligence with Vector Quantization for Image Compression
This paper uses two compression techniques on an image, namely, Vector Quantization (VQ) and Feed Forward Neural Network (FFNN). VQ is used along with K-Mean clustering to initiate the centroids and form the codebook. Th...
Hybrid Kernel Fuzzy Clustering with Feed Lion Neural Network for Missing Data Imputation and Classification
A common issue in many practical applications associated with pattern classification is data incomplete or missing data due to various reasons that differ based on the applications. Missing data imputation is a promising...