Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems
This study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram th...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2011-07-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/11/7/6868/ |
| _version_ | 1798027031203545088 |
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| author | Yang-Lang Chang Shyan-Ming Yuan Da-Cheng Lee Tung-Ju Hsieh Chuan-Yen Chiang Wen-Yew Liang Yen-Lin Chen |
| author_facet | Yang-Lang Chang Shyan-Ming Yuan Da-Cheng Lee Tung-Ju Hsieh Chuan-Yen Chiang Wen-Yew Liang Yen-Lin Chen |
| author_sort | Yang-Lang Chang |
| collection | DOAJ |
| description | This study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram thresholding to extract the pixels of touch blobs obtained from scattered infrared lights captured by a video camera. The advantage of this automatic multilevel thresholding approach is its robustness and adaptability when dealing with various ambient lighting conditions and spurious infrared noises. To extract the connected components of these touch blobs, a connected-component analysis procedure is applied to the bright pixels acquired by the previous stage. After extracting the touch blobs from each of the captured image frames, a blob tracking and event recognition process analyzes the spatial and temporal information of these touch blobs from consecutive frames to determine the possible touch events and actions performed by users. This process also refines the detection results and corrects for errors and occlusions caused by noise and errors during the blob extraction process. The proposed blob tracking and touch event recognition process includes two phases. First, the phase of blob tracking associates the motion correspondence of blobs in succeeding frames by analyzing their spatial and temporal features. The touch event recognition process can identify meaningful touch events based on the motion information of touch blobs, such as finger moving, rotating, pressing, hovering, and clicking actions. Experimental results demonstrate that the proposed vision-based finger detection, tracking, and event identification system is feasible and effective for multi-touch sensing applications in various operational environments and conditions. |
| first_indexed | 2024-04-11T18:44:49Z |
| format | Article |
| id | doaj.art-1054f4d3927e4d549f512bfc5af509d5 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:44:49Z |
| publishDate | 2011-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1054f4d3927e4d549f512bfc5af509d52022-12-22T04:08:51ZengMDPI AGSensors1424-82202011-07-011176868689210.3390/s110706868Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display SystemsYang-Lang ChangShyan-Ming YuanDa-Cheng LeeTung-Ju HsiehChuan-Yen ChiangWen-Yew LiangYen-Lin ChenThis study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram thresholding to extract the pixels of touch blobs obtained from scattered infrared lights captured by a video camera. The advantage of this automatic multilevel thresholding approach is its robustness and adaptability when dealing with various ambient lighting conditions and spurious infrared noises. To extract the connected components of these touch blobs, a connected-component analysis procedure is applied to the bright pixels acquired by the previous stage. After extracting the touch blobs from each of the captured image frames, a blob tracking and event recognition process analyzes the spatial and temporal information of these touch blobs from consecutive frames to determine the possible touch events and actions performed by users. This process also refines the detection results and corrects for errors and occlusions caused by noise and errors during the blob extraction process. The proposed blob tracking and touch event recognition process includes two phases. First, the phase of blob tracking associates the motion correspondence of blobs in succeeding frames by analyzing their spatial and temporal features. The touch event recognition process can identify meaningful touch events based on the motion information of touch blobs, such as finger moving, rotating, pressing, hovering, and clicking actions. Experimental results demonstrate that the proposed vision-based finger detection, tracking, and event identification system is feasible and effective for multi-touch sensing applications in various operational environments and conditions.http://www.mdpi.com/1424-8220/11/7/6868/multi-touch sensingcomputer visionfinger detectionfinger trackingmulti-touch event identification |
| spellingShingle | Yang-Lang Chang Shyan-Ming Yuan Da-Cheng Lee Tung-Ju Hsieh Chuan-Yen Chiang Wen-Yew Liang Yen-Lin Chen Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems Sensors multi-touch sensing computer vision finger detection finger tracking multi-touch event identification |
| title | Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems |
| title_full | Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems |
| title_fullStr | Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems |
| title_full_unstemmed | Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems |
| title_short | Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems |
| title_sort | vision based finger detection tracking and event identification techniques for multi touch sensing and display systems |
| topic | multi-touch sensing computer vision finger detection finger tracking multi-touch event identification |
| url | http://www.mdpi.com/1424-8220/11/7/6868/ |
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