<p>Real-world stimuli can be difficult to manipulate and control in experimental psychology studies. Color information is frequently used as a variable, and researchers often rely on subjective color labels that imprecisely describe the color information within real-world objects. Here, we describe a new toolbox called MATCH (Matching And Transforming Closely Hued objects) that can easily and objectively quantify and manipulate color information within real-world objects to generate object pairs that match in color. MATCH was designed incorporating theoretical frameworks and conceptual understanding from visual cognition research. Additionally, MATCH provides critical information on the distribution of color and the specific color values of any stimulus set. We also present two experimental studies to validate whether MATCH produces images that are consistent with human visual perception. In the first study, we provide evidence that the stimuli generated by MATCH are perceptually closer in color to a reference object compared to human categorization of object–color pairs. In the second study, we investigated the search for real-world objects with distractors generated by MATCH that matched the target object’s color. We found patterns of data that are consistent with current theories of human search behavior. In summary, MATCH allows researchers to carefully control the color of real-world stimuli used in their studies.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

MATCH: A toolbox to assess the primary color of real-world objects and generate color-matching stimuli

  • Jessica N. Goetz,
  • Mark B. Neider

摘要

Real-world stimuli can be difficult to manipulate and control in experimental psychology studies. Color information is frequently used as a variable, and researchers often rely on subjective color labels that imprecisely describe the color information within real-world objects. Here, we describe a new toolbox called MATCH (Matching And Transforming Closely Hued objects) that can easily and objectively quantify and manipulate color information within real-world objects to generate object pairs that match in color. MATCH was designed incorporating theoretical frameworks and conceptual understanding from visual cognition research. Additionally, MATCH provides critical information on the distribution of color and the specific color values of any stimulus set. We also present two experimental studies to validate whether MATCH produces images that are consistent with human visual perception. In the first study, we provide evidence that the stimuli generated by MATCH are perceptually closer in color to a reference object compared to human categorization of object–color pairs. In the second study, we investigated the search for real-world objects with distractors generated by MATCH that matched the target object’s color. We found patterns of data that are consistent with current theories of human search behavior. In summary, MATCH allows researchers to carefully control the color of real-world stimuli used in their studies.