P.131: A Significant Multi‐Touch Algorithm for the Tracking Problem Based on the Hungarian Algorithm

Huang, Shih-Lun; Chen, Charlie Chung‐Ping

doi:10.1002/j.2168-0159.2013.tb06534.x

Cited by 4 publications

(1 citation statement)

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“…After getting a noiseless data map, accurate touch points could be calculated, presented in [19]- [23]. After getting the coordinates of the touch points, the tracking algorithm is used to identify and track the corresponding touch points in two sequential frames, presented in [24]- [29]. The third and fourth steps are pure software-related topics.…”

Section: Introductionmentioning

confidence: 99%

Frequency Hopping and Parallel Driving With Random Delay Especially Suitable for the Charger Noise Problem in Mutual-Capacitive Touch Applications

2019

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Charger noise can cause inaccurate touch points and fake touch points to appear; this can cause a device to behave incorrectly. The intensity of charger noise could be much larger than the intensities of the original touch signals. Furthermore, the frequency of charger noise varies for each different charger. Therefore, industry experts have identified charger noise as the most difficult problem in capacitive touch applications. The demand for a solution to this problem has become crucial for the mobile market. In this paper, we prove that a particular combination of frequency hopping and repeated integration is an effective method to handle this problem. In addition, we propose an efficient discrete Fourier transform-based algorithm to select an effective sensing frequency. We propose parallel driving with random delay to enhance the signal-to-noise ratio (SNR). We show an efficient hardware-software co-design that facilitates the application of our methods in touch ICs. The experimental results show that our methods can increase SNR by over 45 dB and can find an effective sensing frequency fast and dynamically.INDEX TERMS Charger noise, parallel driving, frequency hopping, repeated integration, mutual-capacitive touch.

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Section: Introductionmentioning

confidence: 99%