by far, many stereo-matching techniques have been successfully proposed and applied in digital aerial photogrammetry. however, due to some problems such as large parallaxes, occlusions, geometric deformations, and repetitive patterns in convergent close range images, these methods may not be applicable to the same level of success as that of aerial imagery. in order to overcome these shortcomin...

In this paper we present a simple but effective method for matching two uncalibrated images. Feature points are firstly extracted in each image using a fast multiscale corner detector. Each feature point is assigned with one dominant orientation. The correspondence of feature points is then established by utilizing a multilevel matching strategy. We employ the normalized cross-correlation defin...

In this paper, we present an application of wavelet analysis on feature points matching. Wavelet coefficients which produced by wavelet transform can best display part character of the image. Through the new feature description and feature matching method, we can build a feature point database for each image and improve the efficiency of feature points matching. The experimental results show th...

This paper presents a method for relative orientation using the feature based matching techniques. The interest operator and feature based matching are use to select points and measure parallax for relative orientation automatically. After the feature based matching, a fine least square matching is preformed to achieve high precision. The matched points are then used for the relative orientatio...

This paper proposes an efficient fingerprint recognition algorithm combining phase-based image matching and feature-based matching. In our previous work, we have already proposed an efficient fingerprint recognition algorithm using Phase-Only Correlation (POC), and developed commercial fingerprint verification units for access control applications. The use of Fourier phase information of finger...

Feature points’ matching is a popular method in dealing with object recognition and image matching problems. However, variations of images, such as shift, rotation, and scaling, influence the matching correctness. Therefore, a feature point matching system with a distinctive and invariant feature point detector as well as robust description mechanism becomes the main challenge of this issue. We...

Image feature detection and matching is a fundamental task in image processing and machine vision. In this paper we present novel methods for feature detection and matching. We have used edge points and their accumulated curvature information for feature detection. The detected features are then matched using a new method called “fuzzy-edge based feature matching”. To increase the speed of matc...

Feature-points matching is an important concept in binocular stereo vision. The procession of multi-scale feature-points matching in classical Harris-SIFT algorithm is time-consuming and has high complexity when describing the feature-points. This paper proposed a new improved Harris-SIFT algorithm based on rotation-invariant LBP (Local binary patterns) operator. Firstly, the Harris operator is...

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...