Coloration Quantification has been widely used to study the function and evolution of color signals in animals, birds, reptiles and insects. Current color quantification approaches require the user to manually draw a closed contour that encloses the color patch to be analyzed, using an image editing software. Such manual scoring approaches are extremely time consuming and prone to problems like low repeatability and inter observer errors. There is therefore a need for an automated system for color extraction and quantification. The Automated Coloration quanTification software developed at the IVU lab is a completely automated system that extracts and quantifies animal, bird, reptile and insect coloration in digital images. It has a simple GUI interface that provides the user with different options for storing results and batch processing of images. The various output options include the option to save coloration values in an excel sheet and the option to save an output image that shows a closed contour enclosing the extracted color patch in the original image.
Copyright (c) 2012-2015 Arizona Board of Regents. All Rights Reserved. Contact: Lina Karam ([email protected]) and Tejas Borkar ([email protected]) Image, Video, and Usabilty (IVU) Lab, http://ivulab.asu.edu , Arizona State University This copyright statement may not be removed from any file containing it or from modifications to these files. This copyright notice must also be included in any file or product that is derived from the source files. Redistribution and use of this code in source and binary forms, with or without modification, are permitted provided that the following conditions are met: - Redistribution's of source code must retain the above copyright notice, this list of conditions and the following disclaimer. - Redistribution's in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. - The Image, Video, and Usability Laboratory (IVU Lab, http://ivulab.asu.edu) is acknowledged in any publication that reports research results using this code, copies of this code, or modifications of this code. The code and our papers are to be cited in the bibliography as: T. S. Borkar and L. J. Karam, "Automated Bird Plumage Coloration Quantification in Digital Images," 10th International Symposium on Visual Computing (ISVC), Dec. 2014. https://ivulab.asu.edu/software/coloration/act T. S. Borkar, "Automated Animal Coloration Quantification in Digital Images using Dominant Colors and Skin Classsification," Master's thesis, Arizona State University, December 2013. DISCLAIMER: This software is provided by the copyright holders and contributors "as is" and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall the Arizona Board of Regents, Arizona State University, IVU Lab members, authors or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage.
Note: The ACT Software is available for download at the link below. The provided zip file is password protected. Please email us at [email protected] and we will send you the needed password to unzip the file. The ACT Software is being continuously updated and tested on extensive datasets of different species and you will be informed about new releases as they become available. If you would like to contribute to improving the scope of the ACT software by providing test images of different species used for coloration analysis, please contact us at [email protected].