Name
Title | ||
|---|---|---|
Content-based Image Retrieval using Perceptual Image Hashing and Hopfield Neural Network |
Abstract | ||
|---|---|---|
Unlike the regular usage, hashing methods, which is for cryptography, can be used to extract signatures in relation to the detection of similar images. However, finding a hashing function for detecting image similarity seems to be a challenging task, as the hash code needs to represent the content rather than encrypt it. In this paper, a novel content-based image retrieval method based on perceptual image hashing is proposed. The proposed hashing method creates a signature per image based on image rotation and DCT. The acquired hash code is then used to train a memory model to find similar images among a large number of images. In order to evaluate the proposed method, we compare it with some state-of-the-art methods. The results show that our method provides performance faster and better than the leading competitive methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/mwscas.2018.8623902 | Midwest Symposium on Circuits and Systems Conference Proceedings |
Keywords | Field | DocType |
content-based image retrieval,perceptual image hashing,Hopfield neural network | Pattern recognition,Computer science,Discrete cosine transform,Image retrieval,Encryption,Electronic engineering,Memory model,Artificial intelligence,Hash function,Artificial neural network,Perception,Content-based image retrieval | Conference |
ISSN | Citations | PageRank |
1548-3746 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farzad Sabahi | 1 | 0 | 1.01 |
| M. O. Ahmad | 2 | 1157 | 154.87 |
| M. N. Swamy | 3 | 104 | 18.85 |