Learning Markov Clustering Networks for Scene Text Detection

Abstract

A novel framework named Markov Clustering Network (MCN) is proposed for fast and robust scene text detection. MCN predicts instance-level bounding boxes by firstly converting an image into a Stochastic Flow Graph (SFG) and then performing Markov Clustering on this graph. Our method can detect text objects with arbitrary size and orientation without prior knowledge of object size. The stochastic flow graph encode objects' local correlation and semantic information. An object is modeled as strongly connected nodes, which allows flexible bottom-up detection for scale-varying and rotated objects. MCN generates bounding boxes without using Non-Maximum Suppression, and it can be fully parallelized on GPUs. The evaluation on public benchmarks shows that our method outperforms the existing methods by a large margin in detecting multioriented text objects. MCN achieves new state-of-art performance on challenging MSRA-TD500 dataset with precision of 0.88, recall of 0.79 and F-score of 0.83. Also, MCN achieves realtime inference with frame rate of 34 FPS, which is $1.5\times$ speedup when compared with the fastest scene text detection algorithm.

References in corpus (7)

• TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
• Feature Pyramid Networks for Object Detection
• TextBoxes: A Fast Text Detector with a Single Deep Neural Network
• Scene Text Detection via Holistic, Multi-Channel Prediction
• Synthetic Data for Text Localisation in Natural Images
• Deep Direct Regression for Multi-Oriented Scene Text Detection
• Detecting Oriented Text in Natural Images by Linking Segments

Cited by in corpus (7)

• Pyramid Mask Text Detector
• Deep Discriminative Clustering Analysis
• Scene Text Detection with Supervised Pyramid Context Network
• Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes
• Semantic Correlation Promoted Shape-Variant Context for Segmentation
• Mask is All You Need: Rethinking Mask R-CNN for Dense and Arbitrary-Shaped Scene Text Detection
• Correlation Propagation Networks for Scene Text Detection