Paper
1 July 1992 New method for labeling objects based on convolution
Kent Pu Qing, Robert W. Means
Author Affiliations +
Abstract
Labeling objects in an image is an important step in many application areas such as target tracking, circuit board and IC mask inspection, medical image analysis, environmental analysis, and character recognition. However, in a real time system the speed of the labeling operation is often hindered by bottlenecks. Our new, fast method to perform labeling first obtains the connectivity information for each pixel in the entire image by means of convolution. Then, it uses the connectivity information to assign a temporary label and generate a small equivalence table. Finally, the algorithm uses the equivalence table to obtain the result. The advantage of this algorithm is its ability to exploit high-speed convolutional processors such as HNC's Vision Processor (ViP). Using the ViP and HNC's Balboa 860 coprocessor board, it takes between 36 and 66 milliseconds for most 512 X 512 images of interest (the time taken for the second step is dependent on image content). This type of fast algorithm running in processors such as the ViP, will yield a new wave in imaging processing algorithm development.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kent Pu Qing and Robert W. Means "New method for labeling objects based on convolution", Proc. SPIE 1702, Hybrid Image and Signal Processing III, (1 July 1992); https://doi.org/10.1117/12.60545
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KEYWORDS
Image processing

Convolution

Signal processing

Medical imaging

Surgery

Algorithm development

Image processing algorithms and systems

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