Visual documentation plays a key role in cultural heritage preservation, especially in condition assessment, recording, and monitoring of objects. This research aims at detecting and documenting surface changes on cultural heritage metal objects by employing reflectance transformation imaging (RTI). The objective is to use technological advances in the application of RTI for automated visual documentation of historical metal surfaces. The proposed methodology examines how new algorithms developed to process raw RTI data can be applied to study surface appearance attributes as a function of their angular reflectance. Through visualization of geometric or statistical surface features, global characterization of the appearance attributes and isolation of information are possible. As an illustration of the methodology developed, zinc printing plates exhibiting localized corrosion were examined in terms of condition assessment and surface cleaning monitoring. Data were acquired by employing monochromatic acquisitions using a dome with fully calibrated and motorized functions. Selected features of the surface parameters were then visualized as feature maps. These maps were compared to common RTI visualization methods based on relighting and studying the surface normal. Examination and interpretation of the results indicated that feature maps can provide an enhanced visualization of surface information in comparison to commonly used methods. Geometric maps mainly contain information about the surface topography, whereas statistical maps principally provide information related to changes in the surface reflectance response and thus can separate differences in the light reflection between a metal substrate and its corrosion products. The combination of the extracted information enhances the visualization of an object’s condition and allows the creation of accurate cartographies.