CN105991997A - Capacitive image sensor dead pixel real-time positioning method - Google Patents
Capacitive image sensor dead pixel real-time positioning method Download PDFInfo
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- CN105991997A CN105991997A CN201510100617.5A CN201510100617A CN105991997A CN 105991997 A CN105991997 A CN 105991997A CN 201510100617 A CN201510100617 A CN 201510100617A CN 105991997 A CN105991997 A CN 105991997A
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Abstract
The invention relates to a capacitive image sensor dead pixel real-time positioning method which comprises the steps of (1) adjusting the a capacitor array parameter (the parameter of each capacitor point is consistent), starting a sensor to collect a pair of background images, and generating a histogram, (2) according to the histogram, searching the interval where more than 80% pixels are located, and recording the start gray value and the end gray value of the interval, (3) in the same parameter of a first time collection, starting a sensor to collect a background image again, and judging whether the image gray value is distributed between a start point and an end point in real time to determine whether the point is a deal pixel, and after all point judgment is completed, through reading a mark signal, determining the position of the deal pixel. The capacitive image sensor dead pixel real-time positioning method provided by the invention has the advantages of simple realization and small resource occupation, the positioning detection of the dead pixel can be carried out in leaving a factory, at the same time, the dead pixel generated due to a use environment and other factors can be detected in real time in an application, and the dead pixel is repaired.
Description
Technical field
The invention belongs to technical field of image processing, a kind of method being specifically related to condenser type imageing sensor bad point real-time positioning.
Background technology
Due to production technology deviation and yield issues, causing condenser type imageing sensor dispatching from the factory when, sensor capacitance array point exists random minute
The abnormal electric capacity of cloth, now we define this exception capacitance point is bad point.Bad point exceedes some, can have a strong impact on picture quality, cause image
Valueless.Simultaneously as the capacitor array silicon of condenser type imageing sensor can not cover all of silicon materials as traditional die packing forms so that electricity
Hold collection array to expose for a long time in atmosphere, it is easy to cause capacitor cell to damage, have influence on picture quality the most at last.Qualified sensor makes
During with, often occur because various situations are easily caused the damage of array point.
Knowable to as introduced above, product yield and sensor image quality are directly related with bad point number.How to position bad point position, repair bad point simultaneously
It is present primary study direction, thereby produces condenser type imageing sensor bad point location algorithm and the image repair algorithm of present patent application.
The method of current existing CCD, CMOS camera, capacitance plate and external capacitive fingerprint sensing device detection bad point is all by certain mode
Send into the image of different gray value, judge whether bad point and bad point location positioning according to variation of image grayscale.The most domestic bad point detection and
Repairing, be substantially for capacitance plate, video camera, domestic detection method is mainly by being manually fed into the image of different gray value；And external electric capacity
Formula sensor bad point detection, changes, by the way of at sensor array face coat electrolyte solution (or electrolyte), the background that sensor acquisition arrives
Gray scale, judges whether bad point according to gray-value variation.Existing domestic and international implementation complex procedures, wants electrolyte material and coating precision
Ask high, and existing mode is difficult in batches, carries out bad point detection and location in real time.
Summary of the invention
In order to solve the problem that prior art exists, the present invention proposes the method for condenser type imageing sensor bad point real-time positioning, repaiies for bad point
Realizability condition is provided again, and this implementation realizes simply relative to conventional dead pixel detection method, is prone to batch detection and detects in real time.
The principle of bad point detection to capacitance type sensor image-forming principle analyze, according to image-forming principle design circuit time add testing capacitor (if
Each array point itself can be by adjusting other parameter change sensor background image intensity value, and this testing capacitor device can be without accessing).This test
Electric capacity is mainly used in changing the gray value of sensor background image.Each capacitor cell circuit structure on sensor array is identical, theoretical performance and
Function should equally, and due to the production error of chip, under identical parameters, when gathering background image, image intensity value is distributed near theoretical value little
Scope, this tonal range is normal distribution, and the point within the scope of normal distribution is not labeled as bad point.
The method of the condenser type imageing sensor bad point real-time positioning of the present invention, mainly comprises the steps:
1, adjust capacitor array parameter (each capacitance point parameter is consistent), this parameter makes the main integrated distribution of gray value of background image at sensor
The intermediate grade of tonal range；Start sensor acquisition one width background image, and add up the rectangular histogram of this background image；
2, according to the normal distribution characteristic of image intensity value, the normal distribution searching for more than 80% pixel place on histogram distribution curve is interval,
And record the initial gray value in this interval and terminate gray value；
3, arrange and gather under identical parameters for the first time, starting sensor and again gather a width background image, and each capacitance point pair of real-time judge
Answer gray value whether in normal distribution interval, if the most within the range, be labeled as bad point；After having judged a little, believe by reading labelling
Number, determine the position of bad point.
As a example by capacitive fingerprint sensing device, this patent is described in detail.The condenser type that capacitance type sensor is made up of multiple capacitor cells gathers battle array
Row are constituted.The capacitance difference of fingerprint ridge, paddy is converted into voltage signal or current signal by electric capacity electric discharge by each capacitor cell, and according to necessarily
Period of time T sample voltage value or current value, and this value is sent into comparator analog quantity is converted into numeral 2 values (0/1) signal, these are several
Word 2 value signal bound-time point is the gray value of this point.
When carrying out bad point detection, not accessing finger electric capacity, the gray value affecting capacitor cell generation mainly has reference capacitance, reference voltage and test
Electric capacity, the circuit structure of each capacitor cell and to affect the parameter value of background imaging the same, the background gray levels of the most all array points should one
Sample.But the little deviation produced due to technique, the gray scale that all normal array point gray values should be distributed in a little scope is interval, i.e. normal state is divided
Cloth is interval, and the array point in this gray scale interval is not defined as bad point.
According to above-mentioned principle, the present invention carries out bad point detection judgement according to following steps:
(1) adjusting reference capacitance, reference voltage and testing capacitor, making sensor background image is that gray image (i.e. mainly concentrate by background gray levels
It is distributed in the zone line of sensor tonal gradation).Start sensor acquisition one width background image, and generate the histogram information that this image is corresponding.
(2) according to the distributed area at histogram information search more than 80% pixel place, this interval is normal distribution form, and obtains this interval
Initial tonal gradation start and end tonal gradation end.
(3) with gather under background image identical parameters for the first time, again gather Background, and according to condition start≤image (m, n)≤end,
Whether the gray value that each capacitor cell of real-time judge is corresponding is distributed in normal distribution interval.If condition meets, image (m, n) corresponding electricity
Appearance unit is normal point, is otherwise bad point, and uses this capacitor cell state of 1bit signal labelling (normal point or bad point).Wherein, and image (m, n)
It it is the gray value corresponding to m row, the n-th column capacitance unit.
(4) by reading all marking signals, i.e. can determine that bad point position, follow-up carry out bad point repair process according to bad point position.
A kind of method that the invention provides condenser type imageing sensor bad point real-time positioning, it has the beneficial effect that:
(1) method of the condenser type imageing sensor bad point real-time positioning that the present invention proposes realizes simple, and shared resource is few, it is easy to batch detection
And detect in real time.This bad point detection can carry out detection and localization when dispatching from the factory to bad point, the most in the application can by the method detect in real time by
In making to damage the bad point of the factor generations such as border, and bad point is carried out repair process.
(2) method of the condenser type imageing sensor bad point real-time positioning that the present invention proposes is applicable to capacitance type sensor, inductance type transducer, electricity
Resistive sensors etc. belong to each imageing sensor that image-generating unit circuit structure is identical and image-forming principle is identical with capacitive fingerprint sensing device.If
It is other similar sensor, only need to change the subtest device (testing capacitor) in circuit design, can realize bad by above-mentioned same method
Point location.
Accompanying drawing explanation
Fig. 1 is the flow chart of the present invention a kind of condenser type imageing sensor bad point real-time location method embodiment；
Fig. 2 is the circuit knot of the single capacitor cell of capacitance type sensor of the present invention a kind of condenser type imageing sensor bad point real-time location method embodiment
Structure；
Fig. 3 is the background image histogram distribution schematic diagram of the present invention a kind of condenser type imageing sensor bad point real-time location method embodiment.
Detailed description of the invention
Illustrate that the preferred embodiments of the present invention, specific embodiment described herein only in order to explain the present invention, are not used to below in conjunction with the accompanying drawings
Limit the present invention.
As a example by capacitive fingerprint sensing device, this patent is described in detail.Fig. 2 describes the single electric capacity of capacitance type sensor of one embodiment of the invention
The circuit structure of unit.The capacitance difference of fingerprint ridge, paddy is converted into voltage signal or current signal by electric capacity electric discharge by each capacitor cell, and
According to regular hour cycle T sample voltage value or current value, and analog quantity is converted into by this value feeding comparator (250) numeral 2 values (0/1)
Signal, these digital 2 value signal bound-time points are the gray value of this point.
When carrying out bad point detection, do not access finger electric capacity Cfinger(210) gray value, affecting capacitor cell generation mainly has reference capacitance Cref
(230), reference voltage VrefAnd testing capacitor C (240)test(220), the circuit structure of each capacitor cell and affect the parameter of background imaging
Cref(230)、Vref(240)、Ctest(220) value is the same, and the background gray levels of the most all array points should be equally.Due to technique production
Little deviation, the gray scale that all normal array point gray values should be distributed in a little scope is interval, i.e. normal distribution is interval, not in this gray area
Interior array point is defined as bad point.
With reference to Fig. 1, it is shown that the flow chart of the present invention a kind of condenser type imageing sensor bad point real-time location method embodiment, including:
Step 110, adjusts Cref(230)、Vref(240)、Ctest(220) ash, making sensor background image be gray image, i.e. background image
The main integrated distribution of angle value is in the intermediate grade of sensor tonal range；
Step 120, starts sensor acquisition one width background image, and generates the histogram information that this image is corresponding, be designated as hist, with hist (i)
Represent that gray value is the number of pixels of i, the background image histogram distribution schematic diagram of the embodiment of the present invention as it is shown on figure 3, wherein abscissa i be grey
Degree grade；
Step 130, according to the distributed area at histogram information search more than 80% pixel place, this interval is normal distribution form, in Fig. 3
Shown in normal distribution interval (330), and obtain initial tonal gradation start (350) in this interval and terminate tonal gradation end (360).No
Is a little bad point within this normal distribution interval, and the bad point of the present embodiment is distributed 310 such as Fig. 3, shown in 320,340 on the histogram；
Step 140, with under collection background image identical parameters for the first time, gathers Background again；
Step 150, according to condition start≤image, (m, n)≤end, whether the gray value that each capacitor cell of real-time judge is corresponding is just distributed in
In state distributed area, if (m, n)<(m, n)>end, then (m, n) corresponding capacitor cell is bad point to image to start or image to image, otherwise
For normal capacitor cell, and use this capacitor cell state of 1bit signal labelling (normal point or bad point).Wherein, image (m, n) be m row,
Gray value corresponding to n-th column capacitance unit.
By reading all marking signals, i.e. can determine that bad point position, follow-up carry out bad point repair process according to bad point position.This programme uses
The meansigma methods of two pixels of two, the left side of bad point unit pixel and the right is replaced process to bad point.Such as image, (m n) is bad point, then makes
Image (m, n)=[image (and m-2, n)+image (m-1, n)+image (m+1, n)+image (m+2, n)]/4.
The detailed description and the accompanying drawings of the embodiment of the present invention are only intended to illustrate this that the present invention rather than limit defines by claim and its equivalent
Bright scope.
Claims (5)
1. the method for a condenser type imageing sensor bad point real-time positioning, it is characterised in that including:
Step 1, adjusts capacitor array parameter (each capacitance point parameter is consistent), and this parameter makes the main integrated distribution of gray value of background image pass
The intermediate grade of sensor tonal range；Start sensor acquisition one width background image, and add up the rectangular histogram of this background image；
Step 2, according to the normal distribution characteristic of image intensity value, searches for more than 80% pixel place zone of normal distribution on histogram distribution curve
Between, and record the initial gray value in this interval and terminate gray value；
Step 3, arranges and gathers under identical parameters for the first time, starting sensor and again gather a width background image, and each electric capacity of real-time judge
Point corresponding grey scale value, whether in normal distribution interval, if the most within the range, is labeled as bad point；After having judged a little, marked by reading
Note signal, determines the position of bad point.
2. the method for condenser type imageing sensor bad point real-time positioning as claimed in claim 1, it is characterised in that described capacitor array parameter bag
Include reference capacitance, reference voltage and testing capacitor；Described testing capacitor, is mainly used in changing the gray value of sensor background image.
3. the method for condenser type imageing sensor bad point real-time positioning as claimed in claim 1, it is characterised in that described normal distribution interval is
The range intervals of regular array point gray value, the usually distributed area at more than 80% pixel place；This interval is normal distribution form, this interval
Initial tonal gradation be designated as start, terminate tonal gradation and be designated as end.
4. the method for condenser type imageing sensor bad point real-time positioning as claimed in claim 1, it is characterised in that the condition of described judgement bad point
For: capacitance point corresponding grey scale value not in normal distribution interval, i.e. image (m, n)<start, or image (m, n)>end；
The condition of described judgement normal point is: capacitance point corresponding grey scale value in normal distribution interval, i.e. start≤image (m, n)≤end；
(m n) is the gray value corresponding to m row, the n-th column capacitance unit to described image.
5. the method for condenser type imageing sensor bad point real-time positioning as claimed in claim 1, it is characterised in that described condenser type image sensing
The method of device bad point real-time positioning is applicable to capacitance type sensor, inductance type transducer, resistance sensor etc. and belongs to capacitive fingerprint sensing device
The identical imageing sensor identical with image-forming principle of each image-generating unit circuit structure.
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| CN201510100617.5A CN105991997B (en) | 2015-03-06 | 2015-03-06 | A kind of method that condenser type imaging sensor bad point positions in real time |
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| CN201510100617.5A CN105991997B (en) | 2015-03-06 | 2015-03-06 | A kind of method that condenser type imaging sensor bad point positions in real time |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107644220A (en) * | 2017-09-30 | 2018-01-30 | 上海摩软通讯技术有限公司 | the fingerprint identification method and system of mobile terminal |
| CN107729884A (en) * | 2017-11-22 | 2018-02-23 | 广东欧珀移动通信有限公司 | Fingerprint identification method, mobile terminal and computer-readable recording medium |
| WO2019041243A1 (en) * | 2017-08-31 | 2019-03-07 | 华为技术有限公司 | Method for verifying function of fingerprint sensor and terminal |
| WO2019196009A1 (en) * | 2018-04-10 | 2019-10-17 | 深圳市大疆创新科技有限公司 | Method for detecting defective pixel of image sensor, and photography apparatus, unmanned aerial vehicle and storage medium |
| CN110458827A (en) * | 2019-08-12 | 2019-11-15 | 深圳蓝韵医学影像有限公司 | Detection method, device, equipment and the medium of medical image bad point |
| CN113411567A (en) * | 2021-06-02 | 2021-09-17 | 西北核技术研究所 | Array type image sensor laser damage threshold estimation method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101212703A (en) * | 2006-12-29 | 2008-07-02 | 华晶科技股份有限公司 | Real-time bad image pixel detection method |
| CN102625133A (en) * | 2011-01-31 | 2012-08-01 | 英属开曼群岛商恒景科技股份有限公司 | Detection method of image sensing of bad pixel |
| US20130141595A1 (en) * | 2011-12-02 | 2013-06-06 | Industrial Technology Research Institute | Method for detecting dead pixels and computer program roduct thereof |
| TW201419853A (en) * | 2012-11-09 | 2014-05-16 | Ind Tech Res Inst | Image processor and image dead pixel detection method thereof |
-
2015
- 2015-03-06 CN CN201510100617.5A patent/CN105991997B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101212703A (en) * | 2006-12-29 | 2008-07-02 | 华晶科技股份有限公司 | Real-time bad image pixel detection method |
| CN102625133A (en) * | 2011-01-31 | 2012-08-01 | 英属开曼群岛商恒景科技股份有限公司 | Detection method of image sensing of bad pixel |
| US20130141595A1 (en) * | 2011-12-02 | 2013-06-06 | Industrial Technology Research Institute | Method for detecting dead pixels and computer program roduct thereof |
| TW201419853A (en) * | 2012-11-09 | 2014-05-16 | Ind Tech Res Inst | Image processor and image dead pixel detection method thereof |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019041243A1 (en) * | 2017-08-31 | 2019-03-07 | 华为技术有限公司 | Method for verifying function of fingerprint sensor and terminal |
| CN107644220A (en) * | 2017-09-30 | 2018-01-30 | 上海摩软通讯技术有限公司 | the fingerprint identification method and system of mobile terminal |
| CN107729884A (en) * | 2017-11-22 | 2018-02-23 | 广东欧珀移动通信有限公司 | Fingerprint identification method, mobile terminal and computer-readable recording medium |
| WO2019196009A1 (en) * | 2018-04-10 | 2019-10-17 | 深圳市大疆创新科技有限公司 | Method for detecting defective pixel of image sensor, and photography apparatus, unmanned aerial vehicle and storage medium |
| CN110458827A (en) * | 2019-08-12 | 2019-11-15 | 深圳蓝韵医学影像有限公司 | Detection method, device, equipment and the medium of medical image bad point |
| CN113411567A (en) * | 2021-06-02 | 2021-09-17 | 西北核技术研究所 | Array type image sensor laser damage threshold estimation method |
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