METHOD OF REDUCING COMPUTATION OF PALM REJECTION BY PROJECTING TOUCH DATA

• US 20130265271A1
• Filed: 04/06/2012
• Published: 10/10/2013
• Est. Priority Date: 04/06/2012
• Status: Abandoned Application

• Current Assignee: Silicon Integrated Systems Corporation (Silicon Integrated Systems Corporation Taiwan)
• Original Assignee: Silicon Integrated Systems Corporation (Silicon Integrated Systems Corporation Taiwan)
• Inventors: Kuo, Chin-Hua, Hsu, Jih-Ming
• Application Number:
  US13/441,837
• Publication Number:
  US 20130265271A1
• Time in Patent Office: Days
• US Class Current: 345/174
• CPC Class Codes: G06F 2203/04104 Multi-touch detection in digitiser, i.e. details about the simultaneous detection of a plurality of touching locations, e.g. multiple fingers or pen and finger
• CPC Class Codes: G06F 3/04186 Touch location disambiguation
• CPC Class Codes: G06F 3/0446 using a grid-like structure of electrodes in at least two directions, e.g. using row and column electrodes

Abstract

A method of reducing computation of palm rejection by projecting touch data is disclosed, targeting the handheld devices. The method targets first at obtaining a difference array, followed by extracting maximum values of rows and columns of the difference array to obtain a row projection list and a column projection list respectively. By repeated implementing of mutual capacitance detection, ghost palm blocks can be wiped out from the multiple palm blocks. Once integrating with a local spatial boundary detection algorithm, the sensed signals of intended input located within a rectangular palm block yet beyond a real palm block are consequently detected. The computational algorithm of the palm rejection of this invention is successfully built into the touch panel controller due to its substantially reduced computation.

Claims

1. A method of reducing computation of palm rejection by projecting touch data, the method comprising steps of:

obtaining capacitance raw data of a sensing array having row sensing lines and column sensing lines;

comparing the capacitance raw data with reference raw data to obtain a difference array;

obtaining a row projection list by extracting maximum values of rows the difference array; and

obtaining a column project list by extracting maximum values of columns of the difference array.

2. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 1, wherein the current raw data of the sensing array are obtained by measuring self-capacitances of the respective row sensing lines and the respective column sensing lines.

3. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 1, wherein the current raw data of the sensing array are obtained by measuring mutual capacitances between the row sensing lines and the column sensing lines.

4. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 1, wherein the reference raw data comprises a capacitance matrix computed by a statistic model under a condition that no touch or palm block event occurs on the sensing array.

5. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 4, wherein the reference raw data is computed by using a static calibration procedure.

6. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 4, wherein the reference raw data is computed by using a dynamic calibration procedure.

7. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 1, further comprising a step of determining at least one rectangular palm block by the row projection list and the column projection list.

8. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 7, wherein the step of determining at least one rectangular palm block by the row projection list and the column projection list is to compare the row projection list with a first palm threshold and compare the column projection list with a second palm threshold respectively to form a row palm mask and a column palm mask to determine an extent of the palm block.

9. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 8, wherein the corresponding row palm mask or column palm mask equals to 1 if a sensed signal of a sensing line in the palm block exceeds the palm threshold;

otherwise, the corresponding row palm mask or column palm mask equals to 0 if a sensed signal of a sensing line in the palm block lowers than the palm threshold.

10. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 9, wherein if the number of the adjoined row sensing lines in the palm block is greater than a row-threshold and the number of the adjoined column sensing lines in the palm block is greater than a column-threshold, the sensed signals generated in the palm block are filtered out or neglected.

11. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 9, wherein the number of the adjoined row sensing lines in the palm block multiplied by the number of the adjoined column sensing lines in the palm block is greater than an area-threshold, the sensed signals generated in the palm block are filtered out or neglected.

12. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 1, further comprising a step of filtering out ghost palm blocks from the rectangular palm blocks one after the other, which is accomplished by filtering out ghost palm blocks from the plurality of palm blocks by means of mutual capacitance detection.

13. The method of reducing computation of palm rejection by projecting touch data as claimed in claim 1, further comprising:

detecting the sensed signals fallen within the rectangular palm blocks yet beyond real palm blocks by means of combining a local spatial boundary detection algorithm.