Object recognition has become one of the most active research topics in computer vision in recent years. The set of features extracted from the training image is critical for good object recognition performance. The Scale Invariant Feature Transform (SIFT) was proposed by David Lowe in 1999; the SIFT features are local and effective for object recognition. In this paper we conducted a survey of...

Histogram of orientated gradient (HOG) is widely used as a local feature descriptor in bag of features (BOF) method, whereas, few studies are conducted to discover the relationship between them. In this paper, we exploit this relationship and reveal that the construction method of descriptor in blocks in HOG can be treated as a variant of BOF method. Based on this interpretation, we propose a n...

Targets and objects registration and tracking in a sequence of images play an important role in various areas. One of the methods in image registration is feature-based algorithm which is accomplished in two steps. The first step includes finding features of sensed and reference images. In this step, a scale space is used to reduce the sensitivity of detected features to the scale changes. Afterw...

In this paper, we propose a novel shape descriptor, called Intersection Consistency Histogram (ICH), which is based on a local regularity measure called Intersection Consistency (IC). Comparing with some widely-used state-of-the-art methods in the literature, we show that ICH performs comparable on several widely-used databases. Keywords—Feature Extraction; Feature Description; Shape Description

In this paper, we propose a novel 3D free form surface matching method based on a novel key-point detector and a novel feature descriptor. The proposed detector is based on algebraic surface fitting. By global smooth fitting, our detector achieved high computational efficiency and robustness against nonrigid deformations. For the feature descriptor, we provide algorithms to compute 3D critical ...

Application • A novel image feature descriptor, unit statistical curvature feature (USCF), is proposed based on the statistics of unit curvature distribution to represent the local general invariant features of the image texture. • USCF algorithm had high recognition rate for object images in any size including tiny object images. • USCF is invariant to rotation and linear illumination variatio...

Multi-lingual multi-script often poses various challenges in handwritten numeral classification. In this paper, we present a method for classification of off-line handwritten numerals of three popular Indian scripts. Here we consider Kannada, Telugu and Tamil scripts for our experiment. The features used in the classifier are obtained from local intensity order patter descriptor. For feature co...

With the explosive growth of web multimedia data, how to manage and retrieval the web-scale data more efficiently has become a urgent problem, which expects more efficient low-level feature with low computation. This pressing need brings a huge challenge to the conventional feature. It is urgent to make descriptor more compact and faster and meanwhile remain robust to many different kinds of im...