Wavelet based Video Compression techniques for Industrial monitoring applications

• Published in: Journal of physics. Conference series Vol. 2272; no. 1; pp. 12019 - 12025
• Main Authors: Gunanandhini, S, Kalamani, M, Bhagavathipriya, M, Guru prasath, S
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.07.2022
• Subjects: Acceptable noise levels; Compression ratio; Compression Ratio PSNR; Discrete cosine transform; Discrete Wavelet Transform; Haar; Image quality; Industrial applications; Machine monitoring; Monitoring; Motion perception; Orthogonal Wavelets; Performance evaluation; Physics; Signal to noise ratio; Video Coding; Video compression; Wavelet transforms
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/2272/1/012019

Abstract The principle of industrial machine monitoring and vehicle camera transmission system are focusing on this paper. Video compression is widely used in many industrial applications like continuous monitoring of machines which consumes more storage by capturing every motion detection in machine, hence video coding is highly recommended for video compression without any loss in the actual video. By using wavelet transform delivers the superior localization both in frequency and time domain and its results showcases the better performance while comparing with discrete cosine transform. A comparative analysis has been carried on Video compression using Haar and orthogonal (Daubechies) wavelet. Duplicate coefficients of discrete wavelet transform is reduced by using quantization technique. It aims to attain minimum error while preserving the high peak signal to noise ratio and image quality in the acceptable range. Using PSNR as measure of quality, this paper shows that Daubechies wavelet provides the better quality of video compared to Haar wavelet. Evaluation of performance is depends upon on compression ratio, PSNR, MSE, and SSIM.