Semantic segmentation of images exploiting DCT based features and random forest
- 1 April 2016
- journal article
- research article
- Published by Elsevier in Pattern Recognition
- Vol. 52, 260-273
- https://doi.org/10.1016/j.patcog.2015.10.021
Abstract
No abstract availableKeywords
Funding Information
- STMicroelectronics
This publication has 42 references indexed in Scilit:
- Analysis of the DCT Coefficient Distributions for Document CodingIEEE Signal Processing Letters, 2004
- Multiresolution gray-scale and rotation invariant texture classification with local binary patternsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
- Shape matching and object recognition using shape contextsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
- The global k-means clustering algorithmPattern Recognition, 2002
- A mathematical analysis of the DCT coefficient distributions for imagesIEEE Transactions on Image Processing, 2000
- Shape Quantization and Recognition with Randomized TreesNeural Computation, 1997
- Support-vector networksMachine Learning, 1995
- Distribution shape of two-dimensional DCT coefficients of natural imagesElectronics Letters, 1993
- The JPEG still picture compression standardCommunications of the ACM, 1991
- Statistical distributions of image DCT coefficientsComputers and Electrical Engineering, 1986