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Fast obstacle detection system for the blind using depth image and machine learning |
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| รหัสดีโอไอ | |
| Creator | 1. Surapol Vorapatratorn 2. Atiwong Suchato 3. Proadpran Punyabukkana |
| Title | Fast obstacle detection system for the blind using depth image and machine learning |
| Publisher | Faculty of Engineering, Khon Kaen University |
| Publication Year | 2564 |
| Journal Title | Engineering and Applied Science Research |
| Journal Vol. | 48 |
| Journal No. | 5 |
| Page no. | 593-603 |
| Keyword | Computer vision, Scene understanding, Machine learning, Assistive technology, Visually impaired |
| URL Website | https://www.tci-thaijo.org/index.php/easr/index |
| Website title | Engineering and Applied Science Research |
| ISSN | 2539-6161 |
| Abstract | Our research proposes a novel obstacle detection and navigation system for the blind using stereo cameras with machine learning techniques. The obstacle classification result will navigate users through a difference directional sound patterns via bone conductive stereo headphones. In the first stage, the Semi-Global block-matching technique was used to transform stereo images to depth image which can be used to identify the depth level of each image pixel. Next, fast 2D-based ground plane estimation which was separate obstacle image from the depth image with our Horizontal Depth Accumulative Information (H-DAI). The obstacle image will be then converted to our Vertical Depth Accumulative Information (V-DAI) which was extracted by a feature vector to train the obstacle model. Our dataset consists of 34,325 stereo-gray images in 7 different obstacle class. Our experiment compared various machine learning algorithms (ANN, SVM, Na?ve Bayes, Decision Tree, k-NN and Deep Learning) performance between classification accuracy and prediction speed. The results show that using ANN with our H-DAI and V-DAI reaches 96.45% in obstacle classification accuracy and 23.76 images per second for processing time which is 6.75 times faster than the recently ground plane estimate technique. |
