this study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of tree species identification. to maximize the benefit of such data, the object-based classification was conducted in a mixed forest plantation. two subsets of an ultracam d image were geometrically corrected using aero-triangulation method. some appropriate transformations were perfor...

We consider the problem of object classification by exploiting the hierarchy structure of object categories. Our proposed method first train a collection of binary classifiers to differentiate pairs of object categories at different levels of the object hierarchy. Then we use the outputs of these classifiers and the object hierarchy to define a new image representation. Our experimental results...

In this paper a hierarchical model for pixel clustering and image segmentation is developed. In the model an image is hierarchically structured. The original image is treated as a set of nested images, which are capable to reversibly merge with each other. An object is defined as a structural element of an image, so that, an image is regarded as a maximal object. The simulating of none-hierarch...

as the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. this processing comprises two fundamental and critical steps towar...

An innovative hierarchical image segmentation scheme is reported in this research communication. Unlike static/ spatially divided sub-images, the current innovation concentrates on object level hierarchy for segmentation of gray scale or color images into constituent component/ sub-parts. As for example, a gray scale document image may be segmented (binarized in case of two-level segmentation) ...

This study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of tree species identification. To maximize the benefit of such data, the object-based classification was conducted in a mixed forest plantation. Two subsets of an UltraCam D image were geometrically corrected using aero-triangulation method. Some appropriate transformations were perfor...

In this paper, a level-wise mixture model (LMM) is developed by embedding visual hierarchy with deep networks to support large-scale visual recognition (i.e., recognizing thousands or even tens of thousands of object classes), and a Bayesian approach is used to adapt a pre-trained visual hierarchy automatically to the improvements of deep features (that are used for image and object class repre...

As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...

We give a systematic, abstract formulation of the image normalization method as applied to a general group of image transformations, and then illustrate the abstract analysis by applying it to the hierarchy of viewing transformations of a planar object.

We present a modular architecture for image understanding and active computer vision which consists of the following major components: Sensor and actor interfaces required for data–driven active vision are encapsulated to hide machine–dependent parts; image segmentation is implemented in object–oriented programming as a hierarchy of image operator classes, guaranteeing simple and uniform interf...