Many studies on feature-based search have found that color is preferentially used as a guiding feature. Most of these studies have utilized simple stimuli and the several studies that utilized real-world objects have been limited by the subjective color classification of objects. The current set of studies examined how search was guided by color and color proportions in real-world objects using color histograms to objectively classify color. To bridge the gap between simple stimuli and real-world objects, the first experiment examined how different color compositions in color conjunctions affected search. In the second experiment, real-world objects were objectively classified according to their primary color as determined by a color histogram, which was used to predict behavior. Finally, in the third experiment, real-world objects were classified by both their primary and secondary colors, which again, was used to predict behavior. Across three experiments the results demonstrated that search was guided by both colors of the target and there was more guidance to objects that matched the target's primary color than the target's secondary color. The results showed that theories derived from studying simple stimuli can be applied to more complex stimuli and tools developed in computer vision research can be used as an objective measure.