Method and device for optical detection of the position of an object

• US 7,221,462 B2
• Filed: 06/19/2002
• Issued: 05/22/2007
• Est. Priority Date: 06/21/2001
• Status: Expired due to Fees

• Current Assignee: H2I Technologies Societe Anonyme
• Original Assignee: H2I Technologies Societe Anonyme
• Inventors: Cavallucci, Gilles
• Primary Examiner(s): Nguyen; Sang H.
• Application Number:
  US10/481,560
• Publication Number:
  US 20040246105A1
• Time in Patent Office: 1,798 Days
• Field of Search: 356607-608, 356614-615, 356/622, 356625-629, 356632-640, 250/548, 250/557, 250/572, 250/559.06, 250/559.22, 250/559.24, 250/559.12
• US Class Current: 356/614
• CPC Class Codes: H03K 17/94 characterised by the way in which the control signals are generated
• CPC Class Codes: H03K 17/943 using a plurality of optical emitters or detectors, e.g. keyboard

Abstract

The present invention relates to a method and to a device enabling data to be input, and also to an optical system for detecting the position of an article or a member and suitable for being used (or incorporated) in such a method (or device). The technical field of the invention is that of making keyboards and similar devices enabling manual input of data for processing by a digital computer. The method of the invention for determining the position of an article in a zone uses the steps of structuring a neural network by training, applying data to the input of the structured neural network, the data being the result of converting signals delivered by a plurality of detectors sensitive to illumination of said zone, and determining the position of the article in the zone as a function of at least one data item output by the structured neural network.

Claims

1. A method of determining the position of an article in a zone of a substrate comprising a plurality of zone portions, the method comprising:

placing a plurality of photodetectors each presenting a reception lobe in or around the zone, the set of reception lobes covering all of said zone;

structuring a neural network by supervised training;

applying to the input of the structured neural network data that results from converting signals delivered by said plurality of photodetectors that are sensitive to illumination of said zone; and

determining the position of the article in the zone as a function of at least one data item output by the structured neural network, by determining which of said zone portions has been touched or approached by the article forming an obstacle to the illumination of said zone;

wherein the supervised training is performed by presenting the input of the neural network with several hundreds or thousands of sample vectors in succession, each sample vector comprising a plurality of sample data items resulting from converting signals delivered by said plurality of photodetectors and corresponding to a plurality of different illumination conditions of said zone, and in which the zone is illuminated by a plurality of light emitters each comprising an emission lobe, the set of emission lobes illuminating all of said zone.

2. The method according to claim 1, in which, in order to produce a plurality of different lighting conditions for said zone, a plurality of sources are caused to illuminate said zone in succession, the sources emitting radiation of wavelength(s) situated in the UV, visible, or infrared range.

3. The method according to claim 1, in which useful signals are selected from amongst the signals delivered by the detectors, with signals delivered by one or more blind detectors being eliminated.

4. A device for determining the position of an article in an input or detection zone of a substrate comprising a plurality of zone portions, the device comprising:

a plurality of light sources for illuminating the input or detection zone, each of the plurality of light sources comprising a set of emission lobes for illuminating all of said zone;

a plurality of sensors sensitive to illumination of the zone and delivering electrical signals as a function of said illumination, each of the plurality of sensors comprising a set of reception lobes, the set of reception lobes of each of the plurality of sensors covering all of said zone;

converter means connected to the plurality of sensors and adapted to convert said signals into data; and

classifier means connected to the converter means and adapted to respond to the data that results from the conversion to deliver at least one output data item characteristic of the position of the article in the zone, by determining which portion of the zone the article is touching or is approaching, said classifier means comprising a neural network structured with supervised training obtained by presenting an input of the neural network with several hundreds or thousands of sample vectors in succession, each sample vector comprising a plurality of sample data items resulting from converting signals delivered by said plurality of detectors and corresponding to a plurality of different illumination conditions of said zone by said plurality of light sources.

5. The device according to claim 4, further including light scanning means connected to the plurality of light sources and adapted to cause the plurality of light sources to be switched on in succession.

6. A data input terminal including a device according to claim 4 together with a substrate relative to which the sensors and the sources if any, are mounted in a stationary manner and serving as a support for the input zone.

7. The terminal according to claim 6, having two parallel rows of sensors and two parallel rows of sources disposed in alternation or interleaved with the sensors, and including a mask or cover associated with each sensor to protect it from parasitic light radiation.

8. The device according to claim 4, further comprising means for selecting useful signals, connected to the sensors, and adapted to eliminate signals that are noisy.

9. The device according to claim 8, wherein said means for selecting are adapted to eliminate data or signals by filtering or by weighting.

10. The device according to claim 4, further comprising means for selecting useful data, connected to the converter means, and adapted to eliminate data that result from converting noisy signals.

11. The device according to claim 4, further comprising means for selecting useful data, connected to the classifier means, and adapted to eliminate data that result from converting noisy signals.

12. The device according to claim 4, including a control unit connected to the converter means and to the classifier means, to the selector means, and to the scanner means, to control operation of said means, and also means for storing useful data corresponding to various lighting functions of the zone.

13. The device according to claim 12, wherein said means for storing useful data are in the form of a memory containing a table of useful data grouping together the signal conversion data from each useful sensor in the various steps of lighting the sources in a light scan sequence.