A Format Based Smart Object Tracking Model for Enhance the Quality of Digital Images

• Published in: 2022 International Conference on Computer, Power and Communications (ICCPC) pp. 29 - 34
• Main Authors: Sharon, M, Sharmila, D, Christian, Rachel Evangeline, Shree, Kavya K, Surendiran, J
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.12.2022
• Subjects: digital camera; Digital images; Image coding; image compression; image format; image pixels; Image processing; Image quality; Image resolution; Image restoration; JPEG; lossy transformation; object tracking; Printing; RAW; Transform coding
• DOI: 10.1109/ICCPC55978.2022.10072053

In general, choosing a format for images is a very important factor when choosing a particular type of material in image searches. This is seen as one of the important findings about RAW and JPEG. However, the general majority of experts can imagine the difference between these two forms. JPEG is a common format for photos, and it's handy. If you send images over the web or print images, most often the files are saved in JPG format. However, questions about image integrity have piled up on JPEGs. Of course, this format is described as the most common image compression format and is important for most digital cameras. But this is technically a lossy transformation that degrades the original parameters of the images. This is where the main problem lies, which format to take and save the images creates the problem. In this paper, a smart format enhanced object tracking model was proposed to improve the attributes of the digital images. The camera is initially programmed to make the file smaller by discarding a few pixels. The compression will be more or less depending on the settings you choose. If the file size is set too large, the camera will reject the minimum data. If you need to fit as many views as possible, you set a lower resolution. The proposed model enhances the objects with high compression ratio and provides the better results.