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You will be prompted to upload a text file that contains the lighting directions corresponding to each image in the stack (tab delimited with no header information). In ImageJ, create a stack from the images, convert them from RGB to 32-bit, and then run the script. PHOTOMETRIC STEREO SOFTWARE SERIESTo use, capture a series of raking light images using the same methods described for making an "RTI image". It solves a set of linear equations, using the least squares method, to produce a surface normal vector map. Photometric Stereo: This script is the main workhorse tool. Polynomial fit and polynomial shading corrector What do each of the scripts do? PHOTOMETRIC STEREO SOFTWARE INSTALLTo make full use of these tools you will also need to install two additional ImageJ plugins: The scripts can be accessed in the plugins dropdown menu. ![]() Launch Fiji or "refresh menus" if already running. Getting Started with the Scriptsĭownload the latest version of Fiji and place the scripts into the plugins folder. We use ImageJ (Fiji) because it has a great user interface, it is open source, and provides access to a powerful set of image processing tools that can be readily adapted for extracting surface gradients using the method of photometric stereo, as implemented here, or many other problems related to computational imaging in cultural heritage. al., "Photometric stereo by UV-induced fluorescence to detect protrusions on Georgia O’Keeffe’s paintings" in Metal Soaps in Art – Conservation & Research and on earlier work done with Northwestern's Computational Photo Lab on near lighting models. The scripts were written in Python for use in ImageJ and are based on algorithms detailed in the forthcoming paper: Salvant et. Conversely, new.The set of tools described here are routinely used by the Northwestern University / Art Institute of Chicago Center for Scientific Studies in the Arts (NU-ACCESS) to make surface-shape measurements of works of art and specifically painted surfaces. Other laser triangulation systems use galvanometers to quickly project a moving grid on stationary objects, resulting in high-resolution 3D surface maps. For example, cheap data processing, lasers and optics have facilitated integrated laser triangulation systems for conveyor-based 3D systems that can generate tens of thousands of 2D profiles per second as a step toward creating a 3D object map. While the most challenging modern machine vision solutions that use technologies such as deep learning are being solved in the cloud, cost-effective processing power has relaxed the need for data reduction for the likes of color and 3D applications. Today, microprocessors, graphic processor units (GPUs), field programmable gate arrays (FPGAs) and other computational engines give designers the luxury of more processing power-but processing power isn't infinite as a quick review of modern 3D machine vision methods reveals. This 2D solution might have used mechanical fixtures, for example, to guarantee that "non-flat" objects were always presented the same way, eliminating the need for accurate height information for every pixel, in addition to width and depth location coordinates. Similarly, engineers would develop mechanical fixtures, motion control systems and other methods to solve a traditionally 3D application-such as guiding a robot to pick an object from a moving conveyor-with a 2D machine vision solution. The resulting grayscale images contain less data, making them easier to process quickly. ![]() PHOTOMETRIC STEREO SOFTWARE HOW TOEver since machine vision gained mainstream attention in the 1980s, however, one of the biggest challenges facing machine vision system designers has been how to best reduce the amount of data that needs to be processed to correctly locate, inspect and analyze an object.ĭata reduction meant that machine vision designers tried to find ways to employ lights, filters and cameras to solve color machine vision applications using black-and-white cameras. PHOTOMETRIC STEREO SOFTWARE SOFTWAREMachine vision systems composed of a camera attached to a computer running special image processing software give robots the "sight" they require. Real-world objects have depth, width and height, and automated systems such as robots need to "see" in these three dimensions if they are to operate successfully. ![]()
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