We present a framework to automatically detect and remove shadows in real world scenes
from a single image. Previous works on shadow detection put a lot of effort in designing …

We present a practical framework to automatically detect shadows in real world scenes from
a single photograph. Previous works on shadow detection put a lot of effort in designing …

In recent years, the acquisition of image and video information for processing, analysis,
understanding, and exploitation of the underlying content in various applications, ranging …

Color description is a challenging task because of large variations in RGB values which
occur due to scene accidental events, such as shadows, shading, specularities, illuminant …

Abstract The Hierarchical Conditional Random Field (HCRF) model have been successfully
applied to a number of image labeling problems, including image segmentation. However …

This paper proposes an unsupervised color–texture image segmentation method. In order to
enhance the effects of segmentation, a new color–texture descriptor is designed by …

Monocular depth estimation is very challenging because clues to the exact depth are
incomplete in a single RGB image. To overcome the limitation, deep neural networks rely on …

Clustering validity index (CVI) plays an important role in data partitioning and image
segmentation. In this paper, a new CVI is proposed to perform the color image …

Image segmentation is a very important low-level vision task. It is the perceptual grouping of
pixels based on some similarity criteria. In this article, we have applied spatial fuzzy genetic …

This study is concerned with the problem of shadow detection and removal from single
images of natural scenes. In this work, the authors propose a shadow detection method with …