Purpose

Image annotation plays an important role in image retrieval process, especially when it comes to content-based image retrieval. In order to compensate the intrinsic weakness of machines in performing cognitive task of (human-like) image annotation, leveraging humans’ knowledge and abilities in the form of crowdsourcing-based annotation have gained momentum. Among various approaches for this purpose, an innovative one is integrating the annotation process into the CAPTCHA workflow. In this paper, the current state of the research works in the field and experimental efficiency analysis of this approach are investigated.

Design/methodology/approach

At first, and with the aim of presenting a current state report of research studies in the field, a comprehensive literature review is provided. Then, several experiments and statistical analyses are conducted to investigate how CAPTCHA-based image annotation is reliable, accurate and efficient.

Findings

In addition to study of current trends and best practices for CAPTCHA-based image annotation, the experimental results demonstrated that despite some intrinsic limitations on leveraging the CAPTCHA as a crowdsourcing platform, when the challenge, i.e. annotation task, is selected and designed appropriately, the efficiency of CAPTCHA-based image annotation can outperform traditional approaches. Nonetheless, there are several design considerations that should be taken into account when the CAPTCHA is used as an image annotation platform.

Originality/value

To the best of the authors’ knowledge, this is the first study to analyze different aspects of the titular topic through exploration of the literature and experimental investigation. Therefore, it is anticipated that the outcomes of this study can draw a roadmap for not only CAPTCHA-based image annotation but also CAPTCHA-mediated crowdsourcing and even image annotation.

中文翻译：

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用于众包图像注释的验证码：方向和效率分析

目的

图像标注在图像检索过程中起着重要作用，尤其是在基于内容的图像检索方面。为了弥补机器在执行（类人）图像注释的认知任务方面的内在弱点，以众包为基础的注释形式利用人类的知识和能力已获得动力。在为此目的的各种方法中，一种创新的方法是将注释过程集成到 CAPTCHA 工作流程中。本文对该领域的研究工作现状和该方法的实验效率分析进行了调查。

设计/方法/方法

首先，为了呈现该领域研究的现状报告，提供了全面的文献综述。然后，进行了多项实验和统计分析，以研究基于 CAPTCHA 的图像注释如何可靠、准确和高效。

发现

除了研究基于 CAPTCHA 的图像注释的当前趋势和最佳实践之外，实验结果表明，尽管利用 CAPTCHA 作为众包平台存在一些内在限制，但当挑战（即注释任务）被适当地选择和设计时，基于 CAPTCHA 的图像注释的效率可以优于传统方法。尽管如此，当 CAPTCHA 用作图像注释平台时，应考虑几个设计注意事项。

原创性/价值

据作者所知，这是第一项通过文献探索和实验调查分析标题主题不同方面的研究。因此，预计这项研究的结果不仅可以为基于 CAPTCHA 的图像注释，而且可以为 CAPTCHA 介导的众包甚至图像注释绘制路线图。