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Image matching is widely used in machine vision, computer technology, industry and agriculture and other fields. Matching the characteristics of traditional methods such as SIFT has advantages of compressed information quantity, high precision, but there are also some deficiencies such as the large of calculation, long time, the object to be measured of position should be required accurately and etc...
For the issues that the cropped level of image is detected and the cropped region of image is determined, a new scheme is proposed that is based on SIFT (Scale-invariant feature transform) for the regular clipping operation under the situation of existing original image. Features points of original and testing images are extracted by SIFT algorithm, and the matching are done between the corresponding...
The progress in fields science, information technology and communication have allowed, since the 1970s, developing new electronic aids for the blind in order to overcome the difficulties that the dog and cane do not respond. Among the systems of electronic substitution, are the sensory substitution systems that capture a low-resolution picture of the visual scene and transforming them into an another...
This paper presents a novel athlete detection method in sports video based on local features. Firstly, the framework of the proposed athlete detection system is illustrated. In the proposed system, noise and shadow are eliminated in advance, and the region growing and connectivity analysis process are implemented as well. After carrying out the global motion estimation process, action clips are detected...
Traffic signs automatic recognition was researched in this paper. Traffic signs image preprocessing methods was introduced firstly. Secondly, feature extraction algorithm of traffic signs based on SIFT was elaborated, then a fast SIFT algorithm based on PCA dimensionality reduction was presented to extract the characteristics of traffic signs. Finally, the SVM classifier was studied. A large number...
This paper proposes a novel offline text-independent writer identification method based on scale invariant feature transform (SIFT), composed of training, enrollment, and identification stages. In all stages, an isotropic LoG filter is first used to segment the handwriting image into word regions (WRs). Then, the SIFT descriptors (SDs) of WRs and the corresponding scales and orientations (SOs) are...
SIFT is a well-known feature extract algorithm for image matching. Due to the high dimensionality caused by the feature descriptor, it is too time consuming for real-time image retrieval application with kd-tree. To fast the image retrieval process, we deal with it in two aspects. Firstly, a novel method is proposed to reduce the dimensionality of the sift descriptor, which significantly drops the...
Space-time feature extraction is a recent and popular method used for action recognition. This paper presents a new algorithm to improve the robustness of spatio-temporal feature extraction techniques against the illumination and scale variations. Most of the interest point detectors are sensitive to illumination variations that may cause serious problems in action recognition by finding wrong keypoints...
In the clustering of key points, the ratio of inter-class distance and intra-class distance is enlarged using Normalized SIFT vectors. In order to significantly make the ratio larger, a new normalization method is proposed, which is termed the ¡®normalization method based on seedpoints'. In image preprocessing, for the removal of the object background, a SIFT-based entropy method is given, while the...
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