Image segmentation based on motion/luminance integration and oscillatory correlation

E. Çesmeli, Deliang Wang
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Abstract

An image segmentation method is proposed based on the integration of motion and luminance information. The method is composed of two parallel pathways that process motion and luminance, respectively. Inspired by the visual system, the motion pathway has two stages. The first stage estimates local motion at locations with reliable information The second stage groups locations based on their motion estimates. In the parallel pathway, the input scene is segmented based on luminance. In the subsequent integration stage, motion estimates are refined to obtain the final segmentation result in the motion pathway. For segmentation, LEGION (Locally Excitatory Globally Inhibitory Oscillator Networks) is employed whereby the phases of oscillators are used for region labeling. Results on synthetic and real image sequences are provided.
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基于运动/亮度积分和振荡相关的图像分割
提出了一种基于运动和亮度信息融合的图像分割方法。该方法由两条并行路径组成,分别对运动和亮度进行处理。受视觉系统的启发,运动路径有两个阶段。第一阶段用可靠的信息估计位置的局部运动,第二阶段根据它们的运动估计对位置进行分组。在并行路径中,根据亮度对输入场景进行分割。在随后的积分阶段,对运动估计进行细化,得到运动路径上的最终分割结果。对于分割,使用局部兴奋性全局抑制性振荡网络(LEGION),其中振荡的相位用于区域标记。给出了合成图像序列和真实图像序列的结果。
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