The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illuminati...

The robustness of image features is a very important characteristic for quantitative image analysis. The objective of this paper is to investigate the robustness of various texture features using Hematoxylinstained breast tissue microarray slide by simulating different practical imaging problems including out of focus, magnification changes, illumination variations, noise, compression, distorti...

Many researchers adopt Local Binary Pattern for pattern analysis. However, the long histogram created by Local Binary Pattern is not suitable for a large-scale facial database. This paper presents a simple facial pattern descriptor for facial expression recognition. Local pattern is computed based on local gradient flow from one side to another side through the center pixel in a 3x3 pixels regi...

Local primitives are useful in the analysis, recognition and retrieval of document and patent images. In this paper, local primitives are classified in 4 and 8-directional spaces at optimally detected junction and end points by using a distance based approach. Local primitives are quantized by using a variant of Local Binary Patterns. Spatial relationships between local primitives are establish...

This paper presents a novel method for interest region description. We adopted the idea that the appearance of an interest region can be well characterized by the distribution of its local features. The most well-known descriptor built on this idea is the SIFT descriptor that uses gradient as the local feature. Thus far, existing texture features are not widely utilized in the context of region...

The image space, scale and orientation domains can give valuable clues not seen in either individual of the domains. First we decomposed the face image into different orientation and scale by Gabor filter. Second, we combine local binary pattern analysis with Gabor. It gives a good face representation for recognition. Then we classify in discriminant based up on median histogram distance. The f...

In this paper, an efficient local operator, namely the Local Quantization Code (LQC), is proposed for texture classification. The conventional local binary pattern can be regarded as a special local quantization method with two levels, 0 and 1. Some variants of the LBP demonstrate that increasing the local quantization level can enhance the local discriminative capability. Hence, we present a s...

In this chapter, we propose two novel and curvature-free features: run-lengths of Local Binary Pattern (LBPruns) and Cloud Of Line Distribution (COLD) features for writer identification. The LBPruns is the joint distribution of the traditional run-length and local binary pattern (LBP) methods, which computes the run-lengths of local binary patterns on both binarized images and gray scale images...

This paper presents an approach to derive critical points of a shape, the basis of a Reeb graph, using a combination of a medial axis skeleton and features along this skeleton. A Reeb graph captures the topology of a shape. The nodes in the graph represent critical points (positions of change in the topology), while edges represent topological persistence. We present an approach to compute such...

In this paper LBP and CM methods have been efficiently used for image retrieval for the content based image retrieval (CBIR) system. As LBP method may be sensible to noise in case of comparing neighboring pixels. The drawback of CM is it may be inefficient with too much details image. So it will be better to combine the feature of both method and utilized the property of both the two methods. I...