A downstream algorithm based on extended gradient vector flow field for object segmentation

Cheng‐Hung Chuang

doi:10.1109/TIP.2004.834663

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A downstream algorithm based on extended gradient vector flow field for object segmentation

2004-10-01

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Cheng‐Hung Chuang

Wen‐Nung Lie

DOI：10.1109/TIP.2004.834663

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Abstract

En 中文

For object segmentation, traditional snake algorithms often require human interaction; region growing methods are considerably dependent on the selected homogeneity criterion and initial seeds; watershed algorithms, however, have the drawback of over segmentation. A new downstream algorithm based on a proposed extended gradient vector How (E-GVF) field model is presented in this paper for multiobject segmentation. The proposed flow field, on one hand, diffuses and propagates gradients near object boundaries to provide an effective guiding force and, on the other hand, presents a higher resolution of direction than traditional GVF field. The downstream process starts with a set of seeds scored and selected by considering local gradient direction information around each pixel. This step is automatic and requires no human interaction, making our algorithm more suitable for practical applications. Experiments show that our algorithm is noise resistant and has the advantage of segmenting objects that are separated from the background, while ignoring the internal structures of them. We have tested the proposed algorithm with several realistic images (e.g., medical and complex background images) and gained good results.

Keywords:

gradient vector flow (GVF)

image segmentation

object detection

region growing

snakes

watershed

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