Digital multimedia makes fabricating and copying much easier than ever before. Therefore, it demands efficient and automatic techniques to identify and verify the content of digital multimedia. Image authentication is such a technique to automatically identify whether the query image is a fabrication or a simple copy of the original one. In this paper, we propose a perceptual image authenticati...

The proliferation of digital images creates problems for managing large image databases, indexing individual images, and protecting intellectual property. This paper introduces a novel image indexing technique that may be called an image hash function. The algorithm uses randomized signal processing strategies for a non-reversible compression of images into random binary strings, and is shown t...

Deep hashing methods have received much attention recently, which achieve promising results by taking advantage of the strong representation power of deep networks. However, most existing deep hashing methods learn a whole set of hashing functions independently and directly, while ignore the correlation between different hashing functions that can promote the retrieval accuracy greatly. Inspire...

Huge volumes of images are aggregated over time because many people upload their favorite images to various social websites such as Flickr and share them with their friends. Accordingly, visual search from large scale image databases is getting more and more important. Hashing is an efficient technique to large-scale visual content search, and learning-based hashing approaches have achieved gre...

Image hashing maps an image to a short binary sequence representing the image’s characteristics. This paper proposes a new image hashing method using Zernike moments that are an effective means for extracting robust features from an image. The method is based on rotation invariance of magnitudes and corrected phases of Zernike moments. Similarity between hashes is measured with the Hamming dist...

Hashing has been widely used for large-scale search due to its low storage cost and fast query speed. By using supervised information, supervised hashing can significantly outperform unsupervised hashing. Recently, discrete supervised hashing and deep hashing are two representative progresses in supervised hashing. On one hand, hashing is essentially a discrete optimization problem. Hence, util...

Image hashing is an algorithm used to represent image with a unique value. Hashing methods, which are generally developed search for similar examples of image, have gained new dimension the use deep network structures and better results started be obtained methods. The models consider hash functions independently do not take into account correlation between them. In addition, most existing data...

Perceptual hashing has to deal with the constraints of robustness, accuracy and security. After modeling the process of hash extraction and the properties involved in this process, two different security threats are studied, namely the disclosure of the secret feature space and the tampering of the hash. Two different approaches for performing robust hashing are presented: Random-Based Hash (RB...

Recently, hashing methods have been widely used in large-scale image retrieval. However, most existing hashing methods did not consider the hierarchical relation of labels, which means that they ignored the rich information stored in the hierarchy. Moreover, most of previous works treat each bit in a hash code equally, which does not meet the scenario of hierarchical labeled data. In this paper...

Localization under appearance changes is essential for robots during long-term operation. This paper investigates the problem of place recognition in environments that undergo dramatic visual changes. Our approach builds upon previous work on graph-based image sequence matching and extends it by incorporating a hashing-based image retrieval strategy in case of localization failures or the kidna...