Generating feature detectors with discovery algorithms

M. Zmuda, L. Tamburino, M. Rizki
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Abstract

Traditional techniques for extracting features from images are highly structured processes which require human experts to convert their intuition and experience into algorithms that solve problems such as image classification, target recognition, or assembly line inspection. Intelligent systems such as rule-based expert systems have been used to assist in the development process; however, these approaches still require significant human intervention to achieve acceptable results. This paper describes a system called MORPH which synthesizes complex feature extraction routines using only classification information provided by the image analyst. This system generates a multiplicity of very accurate solutions for several classification tasks.<>
使用发现算法生成特征检测器
从图像中提取特征的传统技术是高度结构化的过程,需要人类专家将他们的直觉和经验转化为解决图像分类、目标识别或装配线检查等问题的算法。基于规则的专家系统等智能系统已被用于协助开发过程;然而,这些方法仍然需要大量的人为干预才能达到可接受的结果。本文描述了一个称为MORPH的系统,该系统仅使用图像分析者提供的分类信息来综合复杂的特征提取例程。该系统为若干分类任务生成了多种非常精确的解决方案
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