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 ...

With the increase of the number of cameras installed across a video surveillance network, the ability of security staffs to attentively scan all the video feeds actually decreases. Therefore, the need for an intelligent system that operates as a tracking system is vital for security personnel to do their jobs well. Tracking people as they move through a camera network with non-overlapping field...

This paper presents a novel approach for visual scene representation, combining the use of quantized color and texture local invariant features (referred to here as visterms) computed over interest point regions. In particular we investigate the different ways to fuse together local information from texture and color in order to provide a better visterm representation. We develop and test our m...

Computational color constancy refers to the problem of computing the illuminant color so that the images of a scene under varying illumination can be normalized to an image under the canonical illumination. In this paper, we adopt a deep learning framework for the illumination estimation problem. The proposed method works under the assumption of uniform illumination over the scene and aims for ...

We aim at predicting a complete and high-resolution depth map from incomplete, sparse and noisy depth measurements. Existing methods handle this problem either by exploiting various regularizations on the depth maps directly or resorting to learning based methods. When the corresponding color images are available, the correlation between the depth maps and the color images are used to improve t...

One of the key tools in applying physics-based models to machine vision has been the analysis of color histograms. In the mid-1980’s it was recognized that the color histogram for a single inhomogeneous surface with highlights will have a planar distribution in color space. I t has since been shown that the colors do not fall randomly in a plane but form clusters a t specific points. Physics-ba...

In real-world applications, service robots need to locate and identify objects in a scene. A range sensor provides a robust estimate of depth information, which is useful to accurately locate objects in a scene. On the other hand, color information is an important property for object recognition task. The objective of this paper is to detect and localize multiple objects within an image using b...

Current character extraction systems for scene images are not robust for most real-world applications. In contrast, the system present here achieves robust performance by using morphological segmentation. This paper describes a new morphological segmentation algorithm { Di erential Top-hats (DTT). In addition, a complete system for extraction of characters from color scene images is presented. ...