This paper presents a novel zero-watermarking scheme, which is robust to geometric distortions and common signal processes. Zero-watemarking technique is different from traditional digital image watermarking, which constructs watermark from its host image, instead of watermark inserting. We construct watermark from low-frequency coefficients in discrete wavelet transform (DWT) domain, which is ...

Even if lots of object invariant descriptors have been proposed in the literature, putting them into practice in order to obtain a robust recognition system face to several perturbations is still a studied problem. After presenting the most commonly used global invariant descriptors, a comparative study permits to show their ability to discriminate between objects with few training. The COIL-10...

In this article existing key points detection and matching methods are observed. The new wavelet transformation based key point detection algorithm is proposed and the descriptor creation is implemented. Keywords—key points, descriptors, SIFT, SURF, wavelet transform.

The concern of the paper is to investigate the application of the Scale-Invariant Feature Transform (SIFT) to the problem of hand gesture recognition by using MATLAB. The algorithm uses modified SIFT approach to match key-points between the query image and the original database of Bare Hand images taken. The extracted features are highly distinctive as they are shift, scale and rotation invaria...

The SIFT (Scale Invariant Feature Transform) descriptor is a widely used method for matching image features. However, perfect scale invariance can not be achieved in practice because of sampling artefacts, noise in the image data, and the fact that the computational effort limits the number of analyzed scale space images. In this paper we propose a modification of the descriptor’s regular grid ...

0167-8655/$ see front matter 2013 Elsevier B.V. A http://dx.doi.org/10.1016/j.patrec.2013.03.021 ⇑ Corresponding author. Tel./fax: +86 29 82667836 E-mail addresses: [email protected], liugz@xjtu Constructing proper descriptors for interest points in images is a critical aspect for local features related tasks in computer vision and pattern recognition. Although the SIFT descriptor has been p...

This paper describes a visual shape descriptor based on the sectors and shape context of contour lines to represent the image local features used for image matching. The proposed descriptor consists of two-component feature vectors. First, the local region is separated into sectors and their gradient magnitude and orientation values are extracted; a feature vector is then constructed from these...

In the light of the deep analyses of subspace recognition and SIFT recognition, a novel image recognition based on subspace and SIFT is proposed to provide a recognition from global features to minutiae features. First, subspace is used to implement coarse image recognition, gaining one or more candidate samples with different identities. Then, a special SIFT recognition environment is designed...

Image-feature matching based on Local Invariant Feature Extraction (LIFE) methods has proven to be successful, and SIFT is one of the most effective. SIFT matching uses only local texture information to compute the correspondences. A number of approaches have been presented aimed at enhancing the image-features matches computed using only local information such as SIFT. What most of these appro...