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A pipelined architecture for image segmentation by adaptive progressive thresholding

机译:通过自适应渐进阈值进行图像分割的流水线架构

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A special purpose VLSI archtecture for the real-time segmentation of endoscopic images is proposed in this paper. The architecture is based on pipelined implementation of a new algorithm named adaptive progressive thresholding (APT) that segments the darkest region of an endoscopic image representing the gastrointestinal lumen. This segmentation process is an extension of a comprehensive statistical technique based on linear discriminant analysis for partitioning the image. The APT algorithm is mapped onto a linear pipelined array of simple processing elements with each element of a particular segment communicating with its neighbours. The APT architecture is partitioned based on various sequential functions involved in the segmentation process and these functional modules are orgainsed in a pipelined fashion according to their hardware feasibility. Currently, a prototype of the VLSI architectute for an image size of 256x256 is designed and built. The functional simulation results obtained in the APT architecture are encouraging.
机译:提出了一种用于内窥镜图像实时分割的专用VLSI架构。该架构基于称为自适应渐进阈值(APT)的新算法的流水线实现,该算法可对代表胃肠道内腔的内窥镜图像的最暗区域进行分割。该分割过程是基于线性判别分析的综合统计技术的扩展,用于对图像进行分区。 APT算法映射到简单处理元素的线性流水线数组,特定段中的每个元素与其邻居进行通信。根据分段过程中涉及的各种顺序功能对APT体系结构进行分区,并根据其硬件可行性以流水线方式来组织这些功能模块。当前,正在设计和建造256x256图像尺寸的VLSI架构原型。在APT架构中获得的功能仿真结果令人鼓舞。

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