In this paper, we propose a novel shape descriptor, called Global Binary Patterns (GBP), based on interpreting intensity values along a direction in an image as binary numbers, converting these binary numbers to their decimal values and concatenating these decimal values as the elements of a vector that is the GBP representation of the shape. Comparing with some widelyused state-of-the-art meth...

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...

© 2013 Woo-han Yun et al. 1021 http://dx.doi.org/10.4218/etrij.13.2013.0054 Automatic facial expression recognition is a widely studied problem in computer vision and human-robot interaction. There has been a range of studies for representing facial descriptors for facial expression recognition. Some prominent descriptors were presented in the first facial expression recognition and analysis ch...

Four novel color Local Binary Pattern (LBP) descriptors are presented in this chapter for scene image and image texture classification with applications to image search and retrieval. Specifically, the first color LBP descriptor, the oRGB-LBP descriptor, is derived by concatenating the LBP features of the component images in an opponent color space — the oRGB color space. The other three color ...

This paper presents a novel image descriptor called Derivative Variation Pattern (DVP) and its application to face and palmprint recognition. DVP captures image variations in both the frequency and the spatial domains. The effects of uncontrolled illumination are compensated in the frequency domain by discarding the illumination affected frequencies. Image pixels are encoded as binary patterns ...

We present a new document image descriptor based on multi-scale runlength histograms. This descriptor does not rely on layout analysis and can be computed efficiently. We show how this descriptor can achieve state-of-theart results on two very different public datasets in classification and retrieval tasks. Moreover, we show how we can compress and binarize these descriptors to make them suitab...

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (L...

This paper presents a texture descriptor for color texture classification specially designed to be robust against changes in the illumination conditions. The descriptor combines a histogram of local binary patterns (LBPs) with a novel feature measuring the distribution of local color contrast. The proposed descriptor is invariant with respect to rotations and translations of the image plane and...

Tensor scale is a morphometric parameter that unifies the representation of local structure thickness, orientation, and anisotropy, which can be used in several computer vision and image processing tasks. In this article, we exploit this concept for binary images and propose a shape salience detector and a shape descriptor – Tensor Scale Descriptor with Influence Zones. It also introduces a rob...

Local Binary Pattern (LBP) is invariant to the monotonic changes in the grey scale domain. This property enables LBP to present a texture descriptor that can be useful in applications dealing with the local illumination changes. However, the existing versions of LBP are not able to handle image illumination changes, especially in outdoor environments. These non-patterned illumination changes di...