Image watermarking is a method that embeds a watermark in the digital image by making small changes in the host data. The embedded watermark must be perceptually invisible and it must be difficult to change or remove it against the intentional or unintentional attacks such as compression, linear and non linear filtering and geometric transformations. In watermarking applications, the robustness...

In this paper, a system based Handwritten Devanagari Character Recognition (HDCR) is proposed. The paper presents an experimental assessment of the efficiency of various methods based on Invariant Moments for handwritten devanagari vowels recognition. The technique is independent of size, slant, orientation, translation and other variations in handwritten vowels. For segmentation of the devanag...

Fingerprint identification is one of the most well-known exposed biometrics, because of their uniqueness, distinctiveness and consistency over time. It is the method of identifying an individual and it can be used in various commercial, government and forensic application, such as, medical records, criminal investigation, cloud computing communication etc. In cloud computing communications, inf...

In this paper, a novel feature-based image watermarking scheme is proposed. Zernike moments which have invariance properties are adopted in the scheme. In the proposed scheme, feature points are first extracted from host image and several circular patches centered on these points are generated. The patches are used as carriers of watermark information because they can be regenerated to locate w...

Content Based Image Retrieval (CBIR) systems based on shape using invariant image moments, viz., Moment Invariants (MI) and Zernike Moments (ZM) are available in the literature. MI and ZM are good at representing the shape features of an image. However, non-orthogonality of MI and poor reconstruction of ZM restrict their application in CBIR. Therefore, an efficient and orthogonal moment based C...

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due t...

In this paper, an algorithm is proposed for the classification of malignancy in mammogram. The types of malignancy can be classified as circumscribed, speculated, architectural distortion, miscellaneous, asymmetry and calcification. Chebyshev moments (CM), being discrete, are capable to combat the discritisation errors as compared to Zernike Moments (ZM), which are continuous moments. It is als...

A texture-based method for fingerprint verification is proposed based on weighted Zernike moments. Zernike moment features are calculated from the region of interest (ROI) which consists of several concentric discs, called multi-discs. Zernike moments of multi-disc ROI are weighted according to the regions of discs. In order to reduce the computational complexity of Zernike moments, the fast Ze...

Image hashing is a new technology in multimedia security. It maps visually identical images to the same or similar short strings called image hashes, and finds applications in image retrieval, image authentication, digital watermarking, image indexing, and image copy detection. This paper presents a perceptual hashing for color images. The input image in RGB color space is firstly converted int...

The goal of this paper is to present the implementation of a Radial Basis Function neural network with built-in knowledge to recognize hand-written characters. The neural network includes in its architecture gates controlled by an attraction/repulsion system of coefficients. These coefficients are derived from a preprocessing stage which groups the characters according to their ascendant, centr...