In this paper, a new approach is presented for improving image quality. It provides a new outlook on how to apply the enhancment methods on images. Image enhancement techniques may deal with the  illumination, resolution, or distribution of pixels values. Issues such as the illumination of the scene and reflectance of objects affect on image captures. Generally, the pixels value of an image is ...

In this paper, we propose a new framework for the dynamic construction of structured visual object/scene detectors for content-based retrieval. In the Visual Apprentice, a user defines visual object/scene models via a multiple-level definition hierarchy: a scene consists of objects, which consist of object-parts, which consist of perceptual-areas, which consist of regions. The user trains the s...

We propose the Adaptive Scene Dependent Filter (ASDF) hierarchy for unsupervised learning of image segmentation, which integrates several processing pathways into a flexible, highly dynamic, and real-time capable vision architecture. It is based on forming a combined feature space from basic feature maps like, color, disparity, and pixel position. To guarantee real-time performance, we apply an...

We propose a family of kernels for structured objectswhich is based on the bag-of-components paradigm. Rather than decomposing each complex object into the single histogram of its components, we use for each object a family of nested histograms, where each histogram in this hierarchy describes the object seen from an increasingly granular perspective. We use this hierarchy of histograms to defi...

In [1] Murray et al. describe a motion processing system, ISOR, which is able to recover the 3D motion and structure of polyhedral objects from an image sequence and goes on, where possible, to recognize the object as one from a database of object models. The system performs a 'bottomup' pass through a vision processing hierarchy in the four stages: (i) Low level Compute visual motion at intens...

In this paper we extend fuzzy analytic hierarchy process into neutrosophic cubic environment. The neutrosophic cubic analytic hierarchy process can be used to manage more complex problems when the decision makers has a number of uncertainty, assigning preferences values to the considered object. We also define the concept of triangular neutrosophic cubic numbers and their operations laws. The a...

Combinatorial geometry is the study of order and incidence properties of groups of geometric features. Ordering properties for point sets in 2-D and 3-D can be seen as a generalization of ordering properties in 1-D and incidences are conngurations of features that are non-generic such as collinearity of points. By deening qualitative shape properties using combinatorial geometry we get a common...

Scene labeling is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in scene labeling frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framewor...

Mathematical morphology interprets images as unions of individually shaped and superpositioned coherent structures. Within this framework, reconstruction filters preserve shapes of image structures that correspond to given base structures, while other structures are removed. This shape-selective transform enables consistent processing of visually perceivable image structures, e.g. of those imag...

In this paper we call for the revival of the study of topological representations in computer vision. Topology allows us to express the connectivity relationships which exist between different primitives in images and in scenes. Although topology was once of significant interest in vision, it has recently become over-shadowed by geometric considerations. We believe that it has a very important ...