An adaptive technique for the extraction of object region and boundary from images with complex environment

Deepthi Valaparla, V. Asari
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引用次数: 8

Abstract

A faster and accurate method for the extraction of object region and boundary from images with complex background environment is presented in this paper. The segmentation procedure begins with the computation of an optimum threshold to distinguish the darker regions in the image. It is an automatic thresholding algorithm that would work under all lighting conditions, where prefixing of threshold value is considered ineffective. The centre of mass of this thresholded region acts as a seed for further processing. Then the object region is obtained by using a region growing technique called integrated neighbourhood search. A quad-structure based technique is used to enhance the speed of region search significantly. A back projection algorithm is used to optimise the search for the pixels belonging to the object region.. A boundary thinning and connecting algorithm based on the application of a novel search window on the preliminary boundary is used to obtain a connected single pixel width boundary. The new method does not need a priori knowledge about the image characteristics. The main advantage of the proposed technique is its high-speed response, which brought an average of 36% decrease in the processing time involved that facilitates real-time analysis of the images.
一种从复杂环境图像中提取目标区域和边界的自适应技术
提出了一种快速、准确地从复杂背景环境图像中提取目标区域和边界的方法。分割过程从计算最佳阈值开始,以区分图像中的较暗区域。它是一种自动阈值分割算法,可以在所有光照条件下工作,其中前缀阈值被认为是无效的。这个阈值区域的质心作为进一步处理的种子。然后利用一种称为综合邻域搜索的区域生长技术获得目标区域。采用基于四结构的技术,显著提高了区域搜索的速度。使用反向投影算法优化搜索属于目标区域的像素。采用一种基于在初步边界上应用新的搜索窗口的边界细化连接算法,得到连通的单像素宽度边界。该方法不需要先验的图像特征知识。该技术的主要优点是其高速响应,平均减少了36%的处理时间,便于对图像进行实时分析。
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