Publication

Vessel Segmentation and Branching Detection using an Adaptive Profile Kalman Filter in Retinal Blood Vessel Structure Analysis

2003
Conference Papers

Abstract

This paper presents an improved tracking based method for retinal vessel segmentation that uses blood vessel morphology to adapt the tracking parameters. The method includes branching detection and avoidance methods. A bi-level threshold method, based on local vessel information, is used for segmentation. Tracking is based on Kalman filtering. The results are compared with existing ground truth. It is concluded that ground truth segmentation is not easily comparable.

Official source

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2003
Conference Papers

Abstract

Official source

Related concepts (29)

Image segmentation

In and computer vision, image segmentation is the process of partitioning a into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.

Object co-segmentation

In computer vision, object co-segmentation is a special case of , which is defined as jointly segmenting semantically similar objects in multiple images or video frames. It is often challenging to extract segmentation masks of a target/object from a noisy collection of images or video frames, which involves object discovery coupled with . A noisy collection implies that the object/target is present sporadically in a set of images or the object/target disappears intermittently throughout the video of interest.

Vehicle tracking system

A vehicle tracking system combines the use of automatic vehicle location in individual vehicles with software that collects these fleet data for a comprehensive picture of vehicle locations. Modern vehicle tracking systems commonly use GPS or GLONASS technology for locating the vehicle, but other types of automatic vehicle location technology can also be used. Vehicle information can be viewed on electronic maps via the Internet or specialized software.

Related publications (4)

Vessel Segmentation and Branching Detection using an Adaptive Profile Kalman Filter in Retinal Blood Vessel Structure Analysis

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Beyond KernelBoost

Multi-layer hierarchical clustering of pedestrian trajectories for automatic counting of people in video sequences

An Implicit Motion Likelihood for Tracking with Particle Filters