A new color descriptor has now been proposed to embed color information into the framework of CENsus Transform histogram (CENTRIST), so that such a state-of-the-art visual descriptor can be further improved to categorize image scenes. In the proposed color CENTRIST descriptor, global structure characteristics are described by both gradients derived from intensity values and color variations bet...

Since Treisman's theory, it has been generally accepted that color is an elementary feature that guides eye movements when looking at natural scenes. Hence, most computational models of visual attention predict eye movements using color as an important visual feature. In this paper, using experimental data, we show that color does not affect where observers look when viewing natural scene image...

We present a method to give (fused) multiband night-time imagery a natural day-time color appearance. For input, the method requires a false color RGB image that is produced by mapping 3 individual bands (or the first 3 principal components) of a multiband nightvision system to the respective channels of an RGB image. The false color RGB nightvision image is transformed into a perceptually deco...

Color constancy refers to the ability to recognize the true color of objects in a scene regardless of the illumination which is incident upon them. While the human visual system is color-constant to a large extent, digital cameras have to rely on fast color balancing algorithms, integrated into their image signal processing (ISP) pipeline, in order to estimate the illumination in a scene and co...

Scene segmentation is a classical problem in computer vision and image processing. Traditionally this problem has been tackled by exploiting only color information from a view of the scene. Recently, a great amount of research has been done in order to develop efficient solutions for depth estimation and tools like modern stereo vision techniques and ToF range cameras allow accurate depth infor...

This thesis addresses the problem in computer vision of recognizing a library of objects in a scene without knowing which objects are in the scene or where they are located. Inherent in this topic is the massive number of possible sets of features from both the scene and the known objects that need to be identified. For an object recognition system to function under these conditions, it must be...

BCET, Gurdaspur Abstract: The color constancy techniques becomes an important pre-processing technique which reduces the effect of the light source on the given image or scene. It is found that light effects lot on a given scene. So effect of the light source may degrades the performance of certain applications a lot like face recognition, object detection, lane detection etc. Color constancy h...

Abstract Aerial scene classification is a challenging problem in understanding high-resolution remote sensing images. Most recent aerial approaches are based on Convolutional Neural Networks (CNNs). These CNN models trained large amount of labeled data and the de facto practice to use RGB patches as input networks. However, importance color within deep learning framework yet be investigated for...

This paper presents new image descriptors based on color, texture, shape, and wavelets for object and scene image classification. First, a new three Dimensional Local Binary Patterns (3D-LBP) descriptor, which produces three new color images, is proposed for encoding both color and texture information of an image. The 3D-LBP images together with the original color image then undergo the Haar wa...