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For the problem that the HAAR descriptors in the speed up robust feature (SURF) algorithm cannot make full use of the information around the feature points, the K-Mean clustering technology is used in this paper to improve the SURF, thus proposing a new face recognition algorithm. Firstly, the problem that the main direction is too dependent on the direction of the local area is avoided by expanding...
An area-based multi-scale method for transformation-invariant descriptor extraction called multi-location feature saliency pattern (MFSP) is proposed in this paper in the context of image matching for change detection and monitoring. Multi-location image descriptors are extracted in salient circular fragments of variable size (scale), which indicate image locations with high intensity contrast, regional...
This paper presents a method to automatically process the education quality assessment quiz test. The propose technique use Pattern Recognition methodology and the final decision is taken using a MLP neural network. The Xj subject's answers are numerically encoded in a descriptor vector VXj. This vector is fed to the net and it decides the Xj's degree of satisfaction or dissatisfaction over the most...
This paper shows a methodology for on-line recognition and classification of pieces in robotic assembly tasks and its application into an intelligent manufacturing cell. The performance of industrial robots working in unstructured environments can be improved using visual perception and learning techniques The object recognition is accomplished using a neuronal network with FuzzyARTMAP architecture...
A novel dissimilarity measure is proposed to perform correspondence image matching for object recognition, image registration and content-based image retrieval. This is a feature-based matching, which supposes image representation (object description) in the form of a set of multi-location descriptor vectors. The proposed measure called intersection matching distance eliminates outlies (false or missing...
Image descriptors are widely adopted structures to match image features. SIFT-based descriptors are collections of gradient orientation histograms computed on different feature regions, commonly divided by using a regular Cartesian grid or a log-polar grid. In order to achieve rotation invariance, feature patches have to be generally rotated in the direction of the dominant gradient orientation. In...
The feature matching is the first step of several computer vision duties. In this paper we provide a new feature detect and matching approach based on statistics of the gradients of the feature region. It is extension of the sift algorithm. The algorithm represented in this paper can be used to perform reliable matching to image sequence, which have larger change in 3D viewpoint and change in illumination...
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