Abstract: Blob analysis is an important part of machine vision system. Fast and efficient Blob analysis is needed to meet real-time demands in industrial applications. This paper presents a fast Blob analysis algorithm based on run-list. The algorithm uses the method of run-lists and dynamic array to build dynamic chain tables for storing two neighbor rows run-coding information. The run list node can be labeled by analyzing its connectivity. This algorithm requires only a single pass over the image, without the need to build an equivalence table and to unite equivalent labels. It can avoid label redundancies present in conventional algorithms. In addition, it can also label holes in blobs. Experimental results show that it can correctly label any Blob regions with complicated shapes and random numbers, and compute blobs features. With faster speed and good stability, the proposed labeling algorithm has been successfully applied in an on-line defect detection system for printed matter.

Key words: Blob analysis, connected component labeling, run-lists, dynamic array