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Connected Components Labeling represents a fundamental step for many Computer Vision and Image Processing pipelines. Since the first appearance of the task in the sixties, many algorithmic solutions to optimize the computational load needed to label an image have been proposed. Among them, block-based scan approaches and decision trees revealed to be some of the most valuable strategies.

However, due to the cost of the manual construction of optimal decision trees and the computational limitations of automatic strategies employed in the past, the application of blocks and decision trees has been restricted to small masks, and thus to 2D algorithms.

With this paper we present a novel heuristic algorithm based on decision tree learning methodology, called Entropy Partitioning Decision Tree (EPDT). It allows to compute near-optimal decision trees for large scan masks. Experimental results demonstrate that algorithms based on the generated decision trees outperform state-of-the-art competitors.

ICPR 2020 MAIN CONFERENCE

A Heuristic-Based Decision Tree for Connected Components Labeling of 3D Volumes

3d volumes

connected components labeling

decision trees

ICPR 2020 is the premier international conference on Pattern Recognition, gathering leading researchers from around the world to present their latest achievements in Pattern Analysis and Recognition, applied Artificial Intelligence and Machine Learning. The topic of the year is " Putting Artificial intelligence to work on Patterns". 
For the first time, ICPR has employed a two-round review process similar to journal submissions, with new papers allowed to be submitted in either the first or second round and papers submitted in the first round and not accepted allowed to be revised and re-submitted for second round review. 

In this edition of the **ICPR 2020** Conference, there are 1407 Oral/Poster presentations organized in five Tracks: 
- Artificial Intelligence, Machine Learning for Pattern Analysis; 
- Biometrics, Human Analysis and Behavior Understanding; Computer Vision, Robotics and Intelligent Systems; 
- Document and Media Analysis; and 
- Image and Signal Processing. 

The **ICPR 2020** Main Conference program also includes 7 Keynotes from prominent world-renowned scientists, 8 Tutorials, 28 Demos, 8 Challenges, 2 Panels, as well as an Industry/Sponsor Exhibition. In addition, 41 Workshops on a range of important current and emerging research topics complete the ICPR 2020 program. 


poster

Combining Deep and Ad-hoc Solutions to Localize Text Lines in Ancient Arabic Document Images

Semi-supervised Deep Learning Techniques for Spectrum Reconstruction

Uniform and Non-uniform Sampling Methods for Sub-linear Time k-means
Clustering

Can you really trust the sensor’s PRNU? How image content might impact the finger vein sensor identification performance

Delivering Meaningful Representation for Monocular Depth Estimation

DARN: Deep Attentive Refinement Network for Liver Tumor Segmentation from 3D CT volume

Silhouette Body Measurement Benchmarks

AVD-Net: Attention Value Decomposition Network For Deep Multi-Agent Reinforcement Learning

UDBNET: Unsupervised Document Binarization Network via Adversarial Game

DAL: A Deep Depth-Aware Long-term Tracker

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A Heuristic-Based Decision Tree for Connected Components Labeling of 3D Volumes

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Combining Deep and Ad-hoc Solutions to Localize Text Lines in Ancient Arabic Document Images

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