Abstract:
Automation for leather grading system is an emerging technology in the leather industries. The leather surface images are rich in texture and results in large file sizes....Show MoreMetadata
Abstract:
Automation for leather grading system is an emerging technology in the leather industries. The leather surface images are rich in texture and results in large file sizes. Hence it needs high storage capacity and the computation time required to process these images is also huge. Image compression has become crucial in relation to processing, storage as well as for transmission. Lossy and lossless are the two compression techniques used widely and lossless compression is preferred for archival purposes. The aim is to present a very efficient image compression technique to reduce the computational complexity of the leather grading system and to store the leather images effectively. Our proposed methodology is to compress an image using second generation wavelets by introducing Lifting Scheme which provides the frame for building the Multiwavelet. The image is compressed by Set Partition in Hierarchical Tree (SPIHT) coding. According to the experimental results, the computational time for leather grading system is considerably reduced by compressing the image. The image is processed 42 % faster than the uncompressed image.
Published in: 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)
Date of Conference: 15-17 December 2016
Date Added to IEEE Xplore: 08 May 2017
ISBN Information:
Electronic ISSN: 2473-943X