Log in
E-mail
Password
Remember
Forgot password ?
Become a member for free
Sign up
Sign up
Settings
Settings
Dynamic quotes 
OFFON

MarketScreener Homepage  >  Equities  >  GRETAI SECURITIES MARKET  >  Egis Technology Inc    6462   TW0006462005

EGIS TECHNOLOGY INC

(6462)
  Report  
SummaryChartsNewsRatingsCalendarCompanyFinancialsConsensusRevisions 
News SummaryMost relevantAll newsOfficial PublicationsSector news

Patent Application Titled “Electronic Device For Distinguishing Between Fingerprint Feature Points And Non-Fingerprint Feature Points And Method For The Same” Published Online (USPTO 20190228201): Egis Technology Inc.

share with twitter share with LinkedIn share with facebook
share via e-mail
0
08/14/2019 | 05:52pm EDT

2019 AUG 14 (NewsRx) -- By a News Reporter-Staff News Editor at Information Technology Business Daily -- According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventors Chiang, Yuan-lin (Taipei City, Tw); Cheng, Yu-chun (Taipei City, Tw), filed on November 19, 2018, was made available online on July 25, 2019.

The assignee for this patent application is Egis Technology Inc. (Taipei City, Taiwan).

Reporters obtained the following quote from the background information supplied by the inventors: “With the advancement of technology, electronic devices have begun to utilize biometrics as a means for identifying users. For example, fingerprint recognition, iris recognition, voiceprint recognition or other recognition techniques have been utilized. Since the equipment required for fingerprint recognition are of lower cost than that of other biometric recognitions, fingerprint recognition has become a common means for identity authentication.

“Currently, fingerprint feature points are the mostly used for fingerprint recognition. For example, the user touches the sensing platform of the fingerprint sensor with the surface of the finger. The fingerprint sensor obtains the user’s fingerprint image by utilizing internal sensing components such as ultrasonic sensors, capacitive sensors, pressure sensors or optical sensors. The electronic device then extracts fingerprint feature points from the fingerprint image and compares the fingerprint feature points to a fingerprint registration template to confirm the identity of the user. During the process of comparison, if the number of the fingerprint feature points being successfully verified (that is, identical or similar feature points can be found in the fingerprint registration template) is more than a default value, the electronic device will determine that the identification performed by the fingerprint sensor is successful, that is, the detected fingerprint image passes the verification. At this time, the electronic device updates the fingerprint registration template of the user according to the fingerprint feature points included in the verified fingerprint image, thereby obtaining more fingerprint feature points of the registered fingerprint.

“However, if there are cracks, stains or fixed patterns on the sensing platform (for example, a film having fixed patterns may be attached on the sensing platform by people of malicious intent), the conventional fingerprint sensor will not only sense the fingerprint patterns, but also sense the cracks, stains or fixed patterns (collectively referred to as non-fingerprint patterns hereinafter). In other words, the sensed fingerprint image will include fingerprint patterns and non-fingerprint patterns. When the conventional electronic device extracts feature points from the fingerprint image, the fingerprint feature points from the fingerprint patterns and the non-fingerprint feature points from the non-fingerprint patterns will both be extracted, and the non-fingerprint feature points may be regarded as the fingerprint feature points. Since the conventional electronic device would update the non-fingerprint feature points into the user’s fingerprint registration template after each successful verification, the user’s fingerprint registration template will have more and more non-fingerprint feature points.

“For example, as shown in FIG. 1A, five fixed patterns (which can also be stains or cracks) are present on the sensing platform, resulting in the sensed fingerprint image 10 containing five non-fingerprint patterns S1, S2, S3, S4, and S5. The conventional electronic device will then extract ten feature points from the fingerprint image 10 (that is, five fingerprint feature points F1, F2, F3, F4 and F5 of the user and five non-fingerprint feature points er1, er2, er3, er4, er5 from non-fingerprint patterns S1-S5 as shown in FIG. 1B). The conventional electronic device will compare the above-mentioned feature points with the user’s fingerprint registration template. Since the above feature points includes fingerprint feature points, the electronic device determines that the fingerprint image 10 passes the verification based on the fingerprint feature points that can be successfully verified, and updates the all of the foregoing feature points into the fingerprint registration template. That is to say, the five non-fingerprint feature points er1-er5 of the non-fingerprint patterns S1-S5 are also updated into the fingerprint registration template.

“When the number of non-fingerprint feature points included in the fingerprint registration template is greater than the above-mentioned default value, anyone would be able to pass the fingerprint verification. This is because any fingerprint images input by any person will contain the identical non-fingerprint patterns, and the conventional electronic device will extract such non-fingerprint feature points for comparing with the non-fingerprint feature points contained in the fingerprint registration template. It will then be determined that the verification is successful, and the fingerprint image will be authenticated.

“Next, the conventional electronic device will further update the fingerprint feature points of such an unauthorized user into the fingerprint registration template. In other words, even if the film attached by people of malicious intent is removed from the sensing platform in the future, the unauthorized user can still pass fingerprint verification through the unauthorized user’s fingerprint feature points that have been updated into the fingerprint registration template.”

In addition to obtaining background information on this patent application, NewsRx editors also obtained the inventors’ summary information for this patent application: “The present disclosure provides an electronic device for distinguishing between fingerprint feature points and non-fingerprint feature points and a method for the same which can prevent non-fingerprint feature points from existing in a fingerprint registration template of a user, so as to prevent fingerprint recognition results from being affected by the non-fingerprint feature points, thereby increasing the safety and accuracy of identity authentication.

“The present disclosure provides a method for distinguishing between fingerprint feature points and non-fingerprint feature points, applicable to an electronic device. The electronic device of the present disclosure comprises a fingerprint sensor, a processor and a storage unit. The method of the present disclosure comprises: obtaining a fingerprint input image by using the fingerprint sensor; extracting a plurality of input feature points from the fingerprint input image by the processor, wherein each of the input feature points has an input position and an input feature vector; obtaining a plurality of reference feature points by the processor, wherein each of the reference feature points has a reference position and a reference feature vector; comparing, by the processor, the plurality of input feature points and the plurality of reference feature points to find at least one input feature point with the input position and the input feature vector being respectively the same as the reference position and the reference feature vector of any of the plurality of reference feature points, and determining the found at least one input feature point as the non-fingerprint feature point.

“The present disclosure provides an electronic device for distinguishing between fingerprint feature points and non-fingerprint feature points, including a fingerprint sensor and a processor. The fingerprint sensor is used for obtaining a fingerprint input image, the processor is electrically coupled to the fingerprint sensor and is configured to perform the following steps: extracting a plurality of input feature points from the fingerprint input image, wherein each of the input feature points has an input position and an input feature vector; obtaining a plurality of reference feature points, wherein each of the reference feature points has a reference position and a reference feature vector; and comparing the plurality of input feature points and the plurality of reference feature points, to find at least one input feature point with the input position and the input feature vector being the same as the reference position and the reference feature vector of any of the plurality of reference feature points, and determining the found at least one input feature point as at least one non-fingerprint feature point.

“In order to further understand the features and technical content of the present disclosure, reference is made to the following detailed instructions and accompanying drawings for the present disclosure, however, the accompanying drawings are provided for reference only and are not intended to limit the present disclosure.

“These and other aspects of the present disclosure will become apparent from the following description of the embodiment taken in conjunction with the following drawings and their captions, although variations and modifications therein may be affected without departing from the spirit and scope of the novel concepts of the disclosure.”

The claims supplied by the inventors are:

“1. A method for distinguishing between fingerprint feature points and non-fingerprint feature points, applicable to an electronic device, the electronic device including a fingerprint sensor, a processor and a storage unit, and the method comprising: obtaining a fingerprint input image by using the fingerprint sensor; extracting a plurality of input feature points from the fingerprint input image by the processor, wherein each of the input feature points has an input position and an input feature vector; obtaining a plurality of reference feature points by the processor, wherein each of the reference feature points has a reference position and a reference feature vector; comparing, by the processor, the plurality of input feature points and the plurality of reference feature points, to find at least one input feature point with the input position and the input feature vector being the same as the reference position and the reference feature vector of any of the plurality of reference feature points, and determining the found at least one input feature point as at least one non-fingerprint feature point.

“2. The method for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 1, wherein for each of the input feature points, the input feature vector is calculated according to the input position and image data in a predetermined region around the input feature point, and for each of the reference feature points, the reference feature vector is calculated according to the reference position and image data in a predetermined region around the reference feature point.

“3. The method for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 2, wherein each of the input feature points has an input angle, and the input feature vector is calculated according to the input angle, and each of the reference feature points has a reference angle, and the reference feature vector is calculated according to the reference angle.

“4. The method for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 1, wherein the step of comparing the plurality of input feature points and the plurality of reference feature points by the processor further comprises: finding at least one input feature point with the input position being different from the reference position of any of the reference feature points; and determining the found at least one input feature point as at least one fingerprint feature point.

“5. The method for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 3, wherein the step of comparing the plurality of input feature points and the plurality of reference feature points by the processor further comprises: finding at least one input feature point with the input position being the same as the reference position of any of the reference feature points and with the input feature vector and the input angle being different from the reference feature vector and the reference angle of any of the reference feature points; for each of the found input feature points, rotating the found input feature point according to a difference value between the input angle of the found input feature point and the reference angle of the reference feature point with the reference position being identical to the input position of the found input feature point, so as to make the input angle of the found input feature point the same as the reference angle; obtaining, according to the reference angle, a rotated input feature vector of the rotated input feature point; determining whether the rotated input feature vector is identical to the reference feature vector; and if the rotated input feature vector is identical to the reference feature vector, determining the input feature point as a non-fingerprint feature point, and if the rotated input feature vector is not identical to the reference feature vector, determining the input feature point as a fingerprint feature point.

“6. The method for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 3, wherein the step of comparing the plurality of input feature points and the plurality of reference feature points by the processor further comprises: finding at least one input feature point with the input position and the input angle being identical to the reference position and the reference angle of any of the reference feature points and with the input feature vector being different from the reference feature vector of any of the reference feature points; and determining the found input feature points as fingerprint feature points.

“7. An electronic device for distinguishing between fingerprint feature points and non-fingerprint feature points, comprising: a fingerprint sensor for obtaining a fingerprint input image; and a processor electrically coupled to the fingerprint sensor, configured to perform the following steps: extracting a plurality of input feature points from the fingerprint input image, wherein each of the input feature points has an input position and an input feature vector; obtaining a plurality of reference feature points, wherein each of the reference feature points has a reference position and a reference feature vector; comparing the plurality of input feature points and the plurality of reference feature points to find at least one input feature point with the input position and the input feature vector being the same as the reference position and the reference feature vector of any of the plurality of reference feature points, and determining the found at least one input feature point as at least one non-fingerprint feature point.

“8. The electronic device for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 7, wherein for each of the input feature points, the input feature vector is calculated according to the input position and image data in a predetermined region around the input feature point, and for each of the reference feature points, the reference feature vector is calculated according to the reference position and image data in a predetermined region around the reference feature point.

“9. The electronic device for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 8, wherein each of the input feature points has an input angle, and the input feature vector is calculated according to the input angle, and each of the reference feature points has a reference angle, and the reference feature vector is calculated according to the reference angle.

“10. The electronic device for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 7, wherein the step of comparing the plurality of input feature points and the plurality of reference feature points by the processor further comprises: finding at least one input feature point with the input position being different from the reference position of any of the reference feature points; and determining the found at least one input feature point as at least one fingerprint feature point.

“11. The electronic device for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 9, wherein the step of comparing the plurality of input feature points and the plurality of reference feature points by the processor further comprises: finding at least one input feature point with the input position being the same as the reference position of any of the reference feature points and with the input feature vector and the input angle being different from the reference feature vector and the reference angle of any of the reference feature points; for each of the found input feature points, rotating the found input feature point according to a difference value between the input angle of the found input feature point and the reference angle of the reference feature point with the reference position being identical to the input position of the found input feature point, so as to make the input angle of the found input feature point the same as the reference angle; obtaining, according to the reference angle, a rotated input feature vector of the rotated input feature point; determining whether the rotated input feature vector is identical to the reference feature vector; and if the rotated input feature vector is identical to the reference feature vector, the input feature point is determined as a non-fingerprint feature point, and if the rotated input feature vector is not identical to the reference feature vector, the input feature point is determined as a fingerprint feature point.

“12. The electronic device for distinguishing between fingerprint feature points and non-fingerprint feature points according to claim 9, wherein the step of comparing the plurality of input feature points and the plurality of reference feature points by the processor further comprises: finding at least one input feature point with the input position and the input angle being identical to the reference position and the reference angle of any of the reference feature points and with the input feature vector being different from the reference feature vector of any of the reference feature points; and determining the found input feature points as fingerprint feature points.”

For more information, see this patent application: Chiang, Yuan-lin; Cheng, Yu-chun. Electronic Device For Distinguishing Between Fingerprint Feature Points And Non-Fingerprint Feature Points And Method For The Same. Filed November 19, 2018 and posted July 25, 2019. Patent URL: http://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220190228201%22.PGNR.&OS=DN/20190228201&RS=DN/20190228201

(Our reports deliver fact-based news of research and discoveries from around the world.)

Copyright © 2019 NewsRx LLC, Information Technology Business Daily, source Technology Newsletters

share with twitter share with LinkedIn share with facebook
share via e-mail
0
Latest news on EGIS TECHNOLOGY INC
08/15Fingerprint Cards swings to second-quarter profit but sales fall
RE
2018EGIS TECHNOLOGY : Showcases Multiple Highly-anticipated Biometrics Solutions at ..
BU
2017EGIS TECHNOLOGY INC. : 2017 Q3 Revenue Report
BU
2017EGIS TECHNOLOGY : to Launch Latest Fingerprint Sensor at 2017 Mobile World Congr..
BU
2017EGIS TECHNOLOGY INC. : 2017 Q1 Revenue Report
BU
2016EGIS TECHNOLOGY : ' Newest Fingerprint Sensor, ET510, Implemented in Samsung's G..
BU
2016EGIS TECHNOLOGY : ' Fingerprint Sensor, ET320, Selected for Samsung Galaxy C7
BU
2016EGIS TECHNOLOGY : ' Fingerprint Sensor, ET320, Selected for Samsung Galaxy A5
BU
More news
Financials (TWD)
Sales 2019 7 699 M
EBIT 2019 1 346 M
Net income 2019 1 467 M
Finance 2019 2 126 M
Yield 2019 5,36%
P/E ratio 2019 14,3x
P/E ratio 2020 9,97x
EV / Sales2019 1,96x
EV / Sales2020 1,44x
Capitalization 17 209 M
Chart EGIS TECHNOLOGY INC
Duration : Period :
Egis Technology Inc Technical Analysis Chart | MarketScreener
Full-screen chart
Income Statement Evolution
Consensus
Sell
Buy
Mean consensus HOLD
Number of Analysts 7
Average target price 278,25  TWD
Last Close Price 251,00  TWD
Spread / Highest target 19,5%
Spread / Average Target 10,9%
Spread / Lowest Target 4,38%
EPS Revisions
Managers
NameTitle
Sen Chou Lo Chairman & General Manager
I Ping Li Chief Financial Officer & Spokesman
Chen Jung Shih Director
Kung Yi Lin Director, Manager & Deputy Spokesman
Ming To Yue Director
Sector and Competitors