Stereo matching of a textured surface is, in principle, ambiguous because of the quasi-repetitive nature of texture. Here, we used a perfectly repetitive texture, namely a sinusoidal grating, to examine human stereo matching for repetitive patterns. Observers matched the depth of a vertical grating segment, 6-deg wide and presented in a rectangular envelope at or near the disparity of the segme...

Many existing ontology matching tools are not well scalable. In this paper, we present the Malasco system, which serves as a framework for reusing existing, non-scalable matching systems on large-scale ontologies. The results achieved with different combinations of partitioning and matching tools are discussed, and optimization techniques are examined. It is shown that the loss of result qualit...

In this paper, we propose a novel hierarchical framework that combines motion and feature information to implement infrared-visible video registration on nearly planar scenes. In contrast to previous approaches, which involve the direct use of feature matching to find the global homography, the framework adds coarse registration based on the motion vectors of targets to estimate scale and rotat...

Due to the limited resources of wireless sensor network, low efficiency of real-time communication scheduling, poor safety defects, and so forth, a queuing performance evaluation approach based on regular expression match is proposed, which is a method that consists of matching preprocessing phase, validation phase, and queuing model of performance evaluation phase. Firstly, the subset of relat...

Schema matching is a crucial task to gather information of the same domain. This is even more the case when dealing with data warehouses, where a large number of data sources are available and require matching and integration. However, the matching process is still largely performed manually or semiautomatically, thus discouraging the use of large scale integration systems. Indeed, these large ...

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...

The ability to handle large scale graph data is crucial to an increasing number of applications. Much work has been dedicated to supporting basic graph operations such as subgraph matching, reachability, regular expression matching, etc. In many cases, graph indices are employed to speed up query processing. Typically, most indices require either super-linear indexing time or super-linear index...

In this paper, we propose a new approach for establishing the correspondence between local invariant features using Bayesian graph matching algorithm. First, we will discuss various local invariant feature detectors and descriptors for scale and affine transformation and illumination changes. Second, we propose an efficient features corresponding method using local invariant features and new gr...

Template matching is one of the most basic techniques in computer vision, where the algorithm should search for a template image T in an image to analyze I. This paper considers the rotation, scale, brightness and contrast invariant grayscale template matching problem. The proposed algorithm uses a sufficient condition for distinguishing between candidate matching positions and other positions ...

The human ear is unique and stability and it has broad application prospects in the field of identity verification. Ear image matching is an important part of the ear recognition, has gained widely research. SIFT(Scale invariant feature transform) descriptor is one of the most effective local features that is used for scale, rotation and illumination invariant. In this paper a fast bi-direction...