نتایج جستجو برای: symmetric local binary patterns
تعداد نتایج: 1094371 فیلتر نتایج به سال:
Recently, we have developed a nonparametric approach to texture analysis based on simple spatial operators like local binary patterns and signed gray level differences. Very good performance has been obtained in various texture classification and segmentation problems. This paper overviews our approach and presents examples to demonstrate its efficiency. Our results suggest that complementary f...
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Three different mechanisms are presented to allow for the representation of 3D surfaces in such a way that key features are retained while at the same time ensuring compatibility with prediction (classification) techniques. The application domain is sheet metal forming. The representations are designed to capture the nature of the surface to be manufactured and predict deformations, known as “s...
In this paper, a novel local texture descriptor termed as Local Block-Difference Pattern (LBDP) is proposed. In conventional LBP, sensitive to intensity change problem will drastically affect the performance due to its simple pixel value comparison mechanism. Different from LBP, the proposed LBDP describes the local textures from a pixel to a block for decreasing the impacts resulting from inte...
We present a novel approach for human gait recognition that inherently combines appearance and motion. Dynamic texture descriptors, Local Binary Patterns from Three Orthogonal Planes (LBP-TOP), are used to describe human gait in a spatiotemporal way. We also propose a new coding of multiresolution uniform Local Binary Patterns and use it in the construction of spatiotemporal LBP histograms. We ...
In this paper, we present and experiment a novel approach for retrieving 3D geometric texture patterns on 2D mesh-manifolds (i.e., surfaces in the 3D space) using local binary patterns (LBP) constructed on the mesh. The method is based on the recently proposed mesh-LBP framework [WBD15]. Compared to its depth-image counterpart, the mesh-LBP is distinguished by the following features: a) inherit...
Local feature detection and description have gained a lot of interest in recent years since photometric descriptors computed for interest regions have proven to be very successful in many applications. In this paper, we propose a novel interest region descriptor which combines the strengths of the well-known SIFT descriptor and the LBP texture operator. It is called the center-symmetric local b...
Accurately detecting pedestrians in images plays a critically important role in many computer vision applications. Extraction of effective features is the key to this task. Promising features should be discriminative, robust to various variations and easy to compute. In this work, we present novel features, termed dense center-symmetric local binary patterns (CS-LBP) and pyramid center-symmetri...
Image hashing allows compression, enhancement or other signal processing operations on digital images which are usually acceptable manipulations. Whereas, cryptographic hash functions are very sensitive to even single bit changes in image. Image hashing is a sum of important quality features in quantized form. In this paper, we proposed a novel image hashing algorithm for authentication which i...
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