For geostationary meteorological satellite (GSMS) remote sensing image registration, high computational cost and matching error are the two main challenging problems. To address these issues, this paper proposes a novel algorithm named slope-restricted multi-scale feature matching. In multi-scale feature matching, images are subsampled to different scales. From a small scale to a large scale, t...

In this paper we study some properties of 3D objects such as compactness, the work done in object transformations and the number of voxels to be moved in order to normalize a similarity measure of an appropriate set of 3D objects. Voxel representation and scale normalization allow us to find the total distance of a set of voxels from one object to another. For these purposes, the comparison of ...

Based on feature matching of car tail text information, a novel approach for vehicle identification is proposed in this paper. Our method creatively implements Scale-Invariant Feature Transform (SIFT) to extract distinctive invariant features from car tail text sub-images, which is a new application of SIFT. In our approach, firstly, the coordinate and the content of a vehicle’s license plate a...

Retrievals of sea ice drift from synthetic aperture radar (SAR) images at high spatial resolution are valuable for understanding kinematic behavior and deformation processes of the ice at different spatial scales. Ice deformation causes temporal changes in patterns observed in sequences of SAR images; which makes it difficult to retrieve ice displacement with algorithms based on correlation and...

Matching Techniques are becoming very attractive research topic. With the development and the use of a large variety of data (e.g. DB schemas, ontologies, taxonomies), in many domains (e.g. libraries, life science, etc), Matching Techniques are called to overcome the challenge of aligning and reconciling theses different interrelated representations. In this paper, we are interested in studying...

A discrete alternative to scale space filtering is presented. The new method provides for fast solutions to problems of spatial containment, filtering and matching, without using arbitrary parameters and smoothing of the input. The discrete space-scale representation is a hierarchical perceptual organization that has concrete applications in computer vision research. Examples of actual implemen...

Numerous deep learning-based object detection methods have achieved excellent performance. However, the performance on small-size and positive negative sample imbalance problems is not satisfactory. We propose a multi-scale feature selective matching network (MFSMNet) to improve of alleviate problems. First, we construct semantic enhancement module (MSEM) compensate for information loss small-s...