基於RGB-D之影像分割方法

Image Segmentation from RGB-D Data

郭弘裕(Hung-Yu Kuo)

指導教授 ： 杜維昌

義守大學/電機資訊學院/資訊工程學系/碩士(2017年)

摘要

影像分割技術是電腦視覺最重要的基礎之一，舉凡圖像檢索、圖形辨識、機器視覺等領域，要先有好的分割技術才能有效進行後續的檢索與辨識工作。傳統的影像分割方法主要根據影像中的彩色資訊為基礎，但隨著平價RGB-D攝影機日益普及，讓我們有了新的影像分割方式。本文採用Kinect攝影機所得到的彩色與深度資訊搭配來進行影像分割，首先對彩色影像進行初步分割，接著使用彩色搭配深度資訊來作鄰近區塊的合併以得到最終的分割成果。藉由深度資訊來彌補以往只單靠顏色作分割的不足，並得到效果合宜的成果。

關鍵字

影像分割 ； 深度攝影機 ； RGB-D影像 ； 超像素

並列摘要

Image segmentation is one of the most important foundations of computer vision. In many applications such as image retrieval, pattern recognition, machine vision and related fields, it is necessary to have a good segmentation technology to facilitate the follow-up retrieval and recognition work. Traditional image segmentation methods are mainly based on the color information in images. With the growing popularity of cheap RGB-D cameras, let us have a new method to do image segmentation. This study uses Kinect camera to get color and depth information for image segmentation. First, image is initially segmented according to color information, followed by the use of color and depth information for the merge of adjacent blocks to get the final segmented results. Use the depth information to make up for the past only color for the lack of segmentation to get the effect of appropriate results.

並列關鍵字

image segmentation ； depth camera ； RGB-D image ； superpixel

參考文獻

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