The main key point of preferential image segmentation is to segment object of user interest based on intensities, boundaries and texture and ignoring the remaining portions. It utilizes a tree of shapes to represent the image content. This representation provides a hierarchical tree for the objects contained in the level sets of the image. The hierarchical structure is utilized to select the ca...

In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from different (granularity) levels are combined to a final (better) segmentation with user-specified operations guiding the segmentation process. Based on these operations the users can pr...

Very high spatial resolution satellite imagery provides data that enables spatially detailed analysis of landscapes. The identification and extraction of information about tree crowns is one such use. Tree crown or canopy cover is one parameter of vegetation structural classification. The estimation of canopy cover has a wide range if uses related to management and policies. Tree crown extracti...

We propose a novel approach that applies global optimal tree-metrics graph cuts algorithm on multi-phase contrast enhanced contrast enhanced MRI for liver tumor segmentation. To address the difficulties caused by low contrasted boundaries and high variability in liver tumor segmentation, we first extract a set of features in multi-phase contrast enhanced MRI data and use color-space mapping to ...

A strong machine learning system should aim to produce the full range of valid interpretations rather than a single mode in tasks involving inherent ambiguity. This is particularly true for image segmentation, in which there are many sensible ways to partition an image into regions. We formulate a tree-structured probabilistic model, the stochastic segmentation tree, that represents a distribut...

Separating text lines in handwritten documents remains a challenge because the text lines are often ununiformly skewed and curved. In this paper, we propose a novel text line segmentation algorithm based on Minimal Spanning Tree (MST) clustering with distance metric learning. Given a distance metric, the connected components of document image are grouped into a tree structure. Text lines are ex...

Although Pulmonary Embolism (PE) is one of the most common causes of unexpected death in the U.S., it may also be one of the most preventable. Images acquired from 16-slice Computed Tomography (CT) machines of contrast-injected patients provide sufficient resolution for the localization and analysis of emboli located in segmental and sub-segmental arteries. After a PE is found, it is difficult ...

Graph cut optimization is one of the standard workhorses of image segmentation since for binary random field representations of the image, it gives globally optimal results and there are efficient polynomial time implementations. Often, the random field is applied over a flat partitioning of the image into non-intersecting elements, such as pixels or super-pixels. In the paper we show that if, ...

Tree is a very common object in nature, thus its segmentation provides quite important information for scene 3D reconstruction. In this paper, we present an algorithm for segmenting trees from a complex scene. The trunk and leaf regions of a tree can be individually identified and the trunk structure of the tree can also be extracted. The proposed algorithm is mainly composed of a preliminary i...