Description: Contour Detection and Hierarchical Image Segmentation (UC Berkeley)
MATLAB/C++混编
Arbela?ez, P., Maire, M., Fowlkes, C., & Malik, J. (2011). Contour Detection and Hierarchical Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(5), 898–916. https://doi.org/10.1109/TPAMI.2010.161(This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on spectral clustering. Our segmentation algorithm consists of generic machinery for transforming the output of any contour detector into a hierarchical region tree. In this manner, we reduce the problem of image segmentation to that of contour detection. Extensive experimental evaluation demonstrates that both our contour detection and segmentation methods significantly outperform competing algorithms. The automatically generated hierarchical segmentations can be interactively refined by user-specified annotations. Computation at multiple image resolutions provides a means of coupling our system to recognition applications.) Platform: |
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Author:aa11285
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Description: Color Reduction and Quantization using k-Means, Fuzzy Clustering (FCM), and SOM Neuarl Network in MATLAB
In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent clustering approaches: (a) k-Means Algorithm, (b) Fuzzy c-Means Clustering (FCM), and (c) Self-Organizing Map Neural Network. The implemented code, uses RGB and HSV color coding, to perform the clustering task, and user can select desired approach of coding. Platform: |
Size: 248832 |
Author:amardz |
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