SIFT Feature Matching Algorithm with Local Shape Context

VF-SIFT: Very Fast SIFT Feature Matching

Feature-based image matching is one of the most fundamental issues in computer vision tasks. As the number of features increases, the matching process rapidly becomes a bottleneck. This paper presents a novel method to speed up SIFT feature matching. The main idea is to extend SIFT feature by a few pairwise independent angles, which are invariant to rotation, scale and illumination changes. Dur...

Video Image Tracing Based on Improved SIFT Feature Matching Algorithm

In this paper, we focus on the extraction problem of the target motion trajectory and make deep research. For Euclidean distance of SIFT feature matching algorithm is not adaptively adjustable, a improved SIFT feature matching algorithm based on multi-objective optimization is proposed. The optimization model is established to reduce mismatch rate, which consider Euclidean distance between corr...

Local Configuration of SIFT-like Features by a Shape Context

The representation of information plays the key role in searching a document. While for text documents it is simple to extract keywords to find a document, for images this task is more challenging. In this paper we discuss different representations of images, point out their advantages and disadvantages and present our proposed method for stable and reliable information extraction to address th...

Improved Characters Feature Extraction and Matching Algorithm Based on SIFT

According to SIFT algorithm does not have the property of affine invariance, and the high complexity of time and space, it is difficult to apply to real-time image processing for batch image sequence, so an improved SIFT feature extraction algorithm was proposed in this paper. Firstly, the MSER algorithm detected the maximally stable extremely regions instead of the DOG operator detected extrem...

Chord Context Algorithm for Shape Feature Extraction