We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by compar...

An efficient descriptor and a complete scheme for removing incorrect correspondences are two essentials for accurate feature points matching in image processing and pattern recognition. This paper proposes a new rigid feature points matching algorithm. First, a new feature descriptor based on the local sharpness distribution is proposed to extract features, which leads to a feature set of extre...

In this paper, we present a novel rotation-invariant and computationally efficient texture descriptor called Dominant Rotated Local Binary Pattern (DRLBP). A rotation invariance is achieved by computing the descriptor with respect to a reference in a local neighborhood. A reference is fast to compute maintaining the computational simplicity of the Local Binary Patterns (LBP). The proposed appro...

Application • A novel image feature descriptor, unit statistical curvature feature (USCF), is proposed based on the statistics of unit curvature distribution to represent the local general invariant features of the image texture. • USCF algorithm had high recognition rate for object images in any size including tiny object images. • USCF is invariant to rotation and linear illumination variatio...

Texture mapping has become the most important method to increase the level of detail for a 3D computer graphics model without increasing its geometric complexity. Procedural texture synthesis methods have been used to generate solid textures for 3D models. These methods use noise functions and generate various solid texture patterns. The number of 3D solid texture databases on the web is increa...

Recent methods for learning similarity between images have presented impressive results in the problem of pair matching (same/notsame classification) of face images. In this paper we explore how well this performance carries over to the related task of multi-option face identification, specifically on the Labeled Faces in the Wild (LFW) image set. In addition, we seek to compare the performance...

In this chapter we examine several concepts related to local feature descriptor design— namely local patterns, shapes, spectra, distance functions, classification, matching, and object recognition. The main focus is local feature metrics, as shown in Figure 4-1. This discussion follows the general vision taxonomy that will be presented in Chapter 5, and includes key fundamentals for understandi...

Local binary pattern (LBP) is an effective texture descriptor which has successful applications in texture classification and face recognition. Many extensions are made for conventional LBP descriptors. One of the extensions is dominant local binary patterns which aim at extracting the dominant local structures in texture images. The second extension is representing LBP descriptors in Gabor tra...