The triplet loss is widely used in learning the local descriptors for image matching. However, existing loss-based methods, like HardNet and DSM, employ point-to-point distance metric, which neglects neighborhood information of descriptors. Considering fact that structures matching would be similar under ideal condition, this paper aims to learn topology-consistent (TCDesc). To end, we first pr...

We propose an efficient image-matching method for deformable-object image matching using discrimination of deformable objects and geometric similarity clustering between feature-matching pairs. A deformable transformation maintains a particular form in the whole image, despite local and irregular deformations. Therefore, the matching information is statistically analyzed to calculate the possib...

In this study, a novel approach which uses combination of steganography and cryptography for hiding information into digital images as host media is proposed. In the process, secret data is first encrypted using the mono-alphabetic substitution cipher method and then the encrypted secret data is embedded inside an image using an algorithm which combines the random patterns based on Space Fillin...

1 This article introduces an approach to matching 2D image segments using approximation spaces. The rough set approach introduced by Zdzis law Pawlak provides a ground for concluding to what degree a particular set of similar image segments is a part of a set of image segments representing a norm or standard. The number of features (color difference and overlap between segments) typically used ...

The use of 2D colour adjacency histograms for image matching in image retrieval scenarios is investigated. We present an algorithm for extracting representative colours from an image and a new method for matching 1D colour histograms and 2D colour adjacency histograms obtained from images quantised using different colour palettes. An experimental evaluation of the matching performance is done.