基于数据压缩的超快速区域生长的图像分割算法  

Image Segmentation Algorithm for Ultra-Fast Region Growth Based on Data Compression

作　　者：许沈榕 XU Shenrong(MatrixTime(Shanghai)Co.,Ltd.,Shanghai 201100,China)

机构地区：[1]聚时科技(上海)有限公司,上海201100

出　　处：《自动化应用》2024年第12期235-237,241,共4页Automation Application

摘　　要：介绍了一种基于数据压缩的超快速区域生长图像分割算法,旨在显著提高图像分割的效率和准确性。传统的区域生长算法在处理大规模图像时通常受计算复杂度和时间方面的限制。为解决该问题,引入数据压缩策略,通过降低数据维度来实现更快速的区域生长。首先,采用先进的数据压缩算法处理图像数据,在有效减小数据体积的同时保持图像质量,为后续的区域生长提供了高效的数据基础。随后,设计了一种快速而准确的整合区域生长算法,考虑了图像特征和邻域关系,实现了对目标区域的迅速和精准识别。实验证明,该方法在提高处理速度的同时保持了分割准确性,尤其在大规模图像处理方面表现显著。基于数据压缩的超快速区域生长方法具有广泛的应用潜力,特别在半导体检测领域,为图像分析和处理提供了高效可行的解决方案,进而为图像分割技术的进一步发展提供了宝贵的见解和方法。This paper introduces an ultra-fast region growing image segmentation algorithm based on data compression,which aims to significantly improve the efficiency and accuracy of image segmentation.The traditional region growing algorithm is usually limited by computational complexity and time in processing large-scale images.To solve this problem,the data compression strategy is introduced to achieve faster regional growth by reducing the data dimension.Firstly,the advanced data compression algorithm is used to process the image data,which can effectively reduce the data volume while maintaining the image quality,and provide an efficient data basis for the subsequent region growth.Then,a fast and accurate integrated region growing algorithm is designed,which considers the image features and neighborhood relationship,and realizes the rapid and accurate recognition of the target region.Experiments show that this method can improve the processing speed and maintain the segmentation accuracy,especially in large-scale image processing.The ultra-fast region growing method based on data compression has a wide application potential.Especially in the field of semiconductor detection,it provides an efficient and feasible solution for image analysis and processing,and provides valuable insights and methods for the further development of image segmentation technology.

关 键 词：数据压缩 多线程 区域生长 图像分割 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]