Research on real-time object labeling methods

Abstract

Real-time multi-objects labeling, which includes segmenting target, picking up features and labeling object automatically, is a study field of Automatic Target Recognition (ATR). Labeling object in an image is a very important step in many application areas such as target scouting and tracking, circuit board and IC mask inspection, environmental and medical image analysis. In this paper, the approaches on object description are classified. Based on the comparison of different methods in many aspects, some representative methods on object labeling, including their basic principles, characteristics, and drawbacks are researched. At the same time, one optimized technique, fast object description on multi-objects labeling, is presented. This fast object labeling algorithm is based on the pixel labeling method. Using the neighboring relationship of binary pixel points in the contiguous scanning lines, this fast approach can complete the pick-up of object labels and the combination of equal target labels during scanning once. Finally, in this approach, the labeling of objects and pick-up of features are accomplished. Experimental results show that the improved algorithm can be used to segment object and label multi-targets, and the performance of the algorithm is fast-speed, practical and simple as well as with the high ability of processing complex patterns.