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Conference Paper
Image Compression based on MR-CNN (Modified Region Convolutional Neural Network)
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- Authors
- Seongmo Park, Byoung Gun Choi, Kwang-Il Oh, S.E. Kim, J.H. Lee, J.J. Lee, Sung Weon Kang
- Issue Date
- 2017-11
- Citation
- International SoC Design Conference (ISOCC) 2017, pp.292-293
- Language
- English
- Type
- Conference Paper
- Project Code
- 17HB1100, Brain-Inspired Neuromorphic Perception and Learning Processor, Lee Joo Hyun
- Abstract
- The proposed algorithm describes compressed image processing based on the Modified Region Convolutional Neural Network (MR-CNN) method. An object extracting unit may classify each of the modified-regions into a background region or an object region on the basis of the degree of pixel changes in the respective set of the modified-regions. There is an efficient compression ratio that can classify an image with each parameter according to the object, text, and background images. The algorithm proposed in the paper improved compression ratio by 10.95% with no degradation compared to the JPEG, and HEVC standards.
- KSP Keywords
- Convolution neural network(CNN), Image Compression, Image processing, Object region, compressed images, compression ratio