REVIEW OF IMAGE FEATURE POINTS DETECTION ALGORITHMS

Multispectral Image Feature Points

This paper presents a novel feature point descriptor for the multispectral image case: Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge ...

Image Surface Extremal Points, new feature points for Image Registration

Automatic Facial Feature Points Detection

This paper presents an algorithm which detects automatically the feature points in a face image. This is a fundamental task in many applications, in particular in an automatic face recognition system. Starting from a frontal face image with a plain background we have effected an image segmentation to detect the different facial components (eyebrow, eyes, nose, mouth and chin). After this we hav...

Algorithms For Feature Selection In Content Based Image Retrieval:A Review

CBIR applies to techniques for retrieving similar images from image databases, based on automated feature selection methods. Feature selection is an important topic in data mining, especially for high dimensional datasets. Feature selection (also known as subset selection) is a process commonly used in machine learning, wherein subsets of the features available from the data are selected for ap...

Image Blur Assessment with Feature Points

Blur is a key factor in the perception of image quality, leading to spread of edges in images. The quantity of feature points extracted from images can represent image shape changes. Compared with sharp images, blurred images tend to contain less feature points, and the reduction of feature points is related to blur. In this paper, we propose a new blind blur assessment metric based on feature ...