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This paper proposes a robust minutiae based fingerprint image hashing technique. The idea is to incorporate the orientation and descriptor in the minutiae of fingerprint images using SIFT-Harris feature points. A recent shape context based perceptual hashing method has been compared against the proposed technique. Experimentally, the proposed technique has been shown to deliver better robustness against...
we propose a hybrid method that integrates the minutiae and their local neighborhood information. This contribution can be seen as a validation step of the minutiae triplets matching performed in a recent algorithm: M3gl. We aim to improve the result of the minutiae triplets matching stage. The characterization of the neighborhood of each triplet is established by a unique feature vector. This descriptor...
Image matching is a key issue in Vision-Based UAV navigation problems. This paper presents an affine and rotation-invariant SIFT features descriptor for matching UAV image with satellite images. The SIFT and ASIFT algorithm are nowadays widely applied for robust image matching, but it also has a high computational complexity. SURF is used for real-time UAV position estimation but is not satisfied...
Biologists collect and analyze phenomic (e.g., anatomical or non-genomic) data to discover relationships among species in the Tree of Life. The domain is seeking to modernize this very time-consuming and largely manual process. We have developed an approach to detect and localize object parts in standardized images of bat skulls. This approach has been further developed for unannotated images by leveraging...
We propose a novel shape descriptor-Included Angle Histogram -for correspondence recovery of graphic vertex and shape-based object recognition. After detecting points local maximal curvature with and the center point of the contour, we construct vectors from the center point to the curvature points. Consequently the point descriptor can be obtained through computing the histograms of included-angles...
A great deal of descriptors for region matching have been proposed in last years. However, an extra step, fitting the irregular regions into fixed shapes, must be implemented in advance when constructing these descriptors on irregular regions. This fitting step can cause great errors, and thus will result in poor matching. Base on inner product and exterior product, this paper develops a method for...
Finding correspondences between feature points is one of the most relevant problems in the whole set of visual tasks. In this paper we address the problem of matching a feature vector (or a matrix) to a given subspace. Given any vector base of such a subspace, we observe a linear combination of its elements with all entries swapped by an unknown permutation. We prove that such a computationally hard...
This paper proposes an angular invariant feature for registration procedure to perform reliable matching between a given model shape and a data shape. The feature is defined by a k-dimensional vector with k angles between the normal vector of each point and its k-nearest-neighbors individually. The feature is invariant to scale transformation, rotation transformation. Particularly, when we register...
A new image feature called Harris feature vector is defined in this paper, which effectively describes the image gradient distribution. By computing the mean and the standard deviation of the Harris feature vector in key point neighborhood, a novel descriptor for key points matching is constructed, which is invariant to image rigid transformation and linear intensity change. Experimental evidence...
Based on the study of patterns used in many fast algorithms for the block-matching motion estimation (BMME), a new search pattern, LP (line search pattern), was introduced in this paper. LP is also a simplified square search pattern as TP(Triangle search Pattern). By combing LP with DP(diamond search pattern), a fast BMA (BMME Algorithm), DLS (diamond-line search), was also proposed in this paper...
We perform shape matching by transforming the problem of establishing shape correspondences into an image registration problem. At each vertex on the shape, we calculate a shape feature and encode this feature as image intensity at appropriate positions in the image domain. Calculating multiple features at each vertex and encoding them into the image domain results in a vector-valued feature image...
Shape matching is one of the more significant research topics in the fields of computer vision, pattern recognition and machine learning. Successful shape matching algorithms/ methods has a high potential for a wide variety of practical applications. In this paper, we present our effort on using linear projection methods for static hand sign recognition in Malaysian sign language. PCA and LPP methods...
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