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Encrypted image classification based on multilayer extreme learning machine
- Source :
- Multidimensional Systems and Signal Processing. 28:851-865
- Publication Year :
- 2016
- Publisher :
- Springer Science and Business Media LLC, 2016.
-
Abstract
- Nowadays, numerous corporations (such as Google, Baidu, etc.) require an efficient and effective search algorithm to crawl out the images with queried objects from databases. Moreover, privacy protection is a significant issue such that confidential images must be encrypted in corporations. Nevertheless, decrypting and then classifying millions of encrypted images becomes a heavy burden to computation. In this paper, we proposed an encrypted image classification framework based on multi-layer extreme learning machine that is able to directly classify encrypted images without decryption. Experiments were conducted on popular handwritten digits and letters databases. Results demonstrate that the proposed framework is secure, efficient and accurate for classifying encrypted images.
- Subjects :
- Contextual image classification
business.industry
Computer science
Applied Mathematics
Computation
Privacy protection
020206 networking & telecommunications
02 engineering and technology
Encryption
computer.software_genre
Computer Science Applications
Artificial Intelligence
Hardware and Architecture
Search algorithm
Signal Processing
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Confidentiality
Data mining
business
computer
Software
Information Systems
Extreme learning machine
Subjects
Details
- ISSN :
- 15730824 and 09236082
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- Multidimensional Systems and Signal Processing
- Accession number :
- edsair.doi...........2fcbd1e1dd8567ce6f1084575083eb41