Testing Dataset for Accelerated Superpixel Image Segmentation with a Parallelized DBSCAN Algorithm

This dataset consists of the processing output from the comparison of superpixel algorithms for the article "Accelerated Superpixel Image Segmentation with a Parallelized DBSCAN Algorithm". Division of images into groups of perceptually similar and proximate pixels is a necessary pre-processing step in many computer graphics algorithms such as image segmentation, classification, object tracking, and motion estimation. By reducing the number of operational units being processed into superpixels, the algorithms can run more efficiently and hence faster. The article describes the development of a new superpixel algorithm and compares its performance to the optimized algorithms in the OpenCV library and others selected based on their processing speed and quality. The new algorithm's segmentation performance in terms of Boundary Recall, Under-Segmentation Error, and Achievable Segmentation Accuracy are comparable to the OpenCV algorithms while performing between 4-135 times faster. The original images were obtained from the Berkeley Segmentation Data Set and Benchmarks 500 (BSDS500) and should be placed in the root folder of the dataset (*.jpg), while the ground truth MATLAB files (*.mat) should be placed in the folder "GroundTruth". The folders "GroundTruthBoundaries" and "GroundTruthSegmentation" are generated from the ground truth files and are used by the software to compare with the corresponding outputs from the respective superpixel algorithms in "OutlineImages" and "SegmentationImages" to generate the segmentation metrices. The folders "NoiseOutlineImages" and "NoiseSegmentationImages" are outputs generated from BSDS500 images that have increasing amounts of added uniform (salt-and-pepper) noise. The "Results" folder contains the output Excel spreadsheet and MATLAB script files to generate the graphs from the article. The "Images" sub-folder in the Results folder contains selected processed and segmented images that were used for visual comparison. The "ScanSegment" folder contains intermediate processing files, and the segmented output for CRS, ERS, ETPS, RT-DBSCAN (FastSuperpixel), and the new algorithm (ScanSegment). Segmentation output for the OpenCV algorithms are not included due to space limitations, but can be generated from the software.