CN105136733A - Near-infrared defect analyzing system for capsules - Google Patents

Near-infrared defect analyzing system for capsules Download PDF

Info

Publication number
CN105136733A
CN105136733A CN201510535359.3A CN201510535359A CN105136733A CN 105136733 A CN105136733 A CN 105136733A CN 201510535359 A CN201510535359 A CN 201510535359A CN 105136733 A CN105136733 A CN 105136733A
Authority
CN
China
Prior art keywords
capsule
flaw
subset
equipment
infrared
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201510535359.3A
Other languages
Chinese (zh)
Inventor
李学新
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Li Xiying
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to CN201510535359.3A priority Critical patent/CN105136733A/en
Publication of CN105136733A publication Critical patent/CN105136733A/en
Pending legal-status Critical Current

Links

Landscapes

  • Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)

Abstract

The invention relates to a near-infrared defect analyzing system for capsules. The near-infrared defect analyzing system comprises near-infrared data collecting equipment, defect detecting equipment and an ARM11 processor, wherein the near-infrared data collecting equipment is used for collecting near-infrared images for all the capsules, the defect detecting equipment is connected with the near-infrared data collecting equipment and used for extracting defect information of the corresponding capsules based on the collected near-infrared images, and the ARM11 processor is connected with the defect detecting equipment and used for determining whether the capsules corresponding to the defect information are defective capsules or not. By means of the near-infrared defect analyzing system, the capsules to be checked are detected in a near-infrared detection mode, and the accuracy of capsule detection is improved.

Description

Capsule near infrared defect analyses system
Technical field
The present invention relates near infrared detection field, particularly relate to a kind of capsule near infrared defect analyses system.
Background technology
For capsule, its quality directly affects the drug quality of its encapsulation.In order to improve drug quality, extremely important to the Defect Detection of capsule in capsule manufacture process.
But in prior art, there is following flaw in the check system of capsule flaw: the mode efficiency of (1) manual detection is low, easily undetected; (2) mode of mechanical detection generally adopts the mode of image recognition, but its capsule splits Threshold selection difficulty used, lacks effective capsule Defect Detection mechanism.
For this reason, the present invention proposes a kind of capsule near infrared defect analyses system, the mode of choice for use mechanical detection, can improve existing mechanical detection scheme, improve the precision of capsule Iamge Segmentation and capsule Defect Detection, thus provide important reference data for the subsequent production of capsule producer.
Summary of the invention
In order to solve the technical matters that prior art exists, the invention provides a kind of capsule near infrared defect analyses system, adopt the mode of near infrared detection, by the preference pattern of adaptivenon-uniform sampling threshold value, improve the accuracy of capsule Iamge Segmentation, meanwhile, adopt the quantity of the pixel calculating pixel value non-zero in flaw image to determine whether capsule exists flaw, ensure that the reliability of capsule defect analyses.
According to an aspect of the present invention, provide a kind of capsule near infrared defect analyses system, described analytic system comprises near infrared data acquisition equipment, Defect Detection equipment and ARM11 processor, described near infrared data acquisition equipment is used for carrying out near-infrared image collection to every capsule, described Defect Detection equipment is connected with described near infrared data acquisition equipment, for extracting the flaw information of corresponding capsule based on the near-infrared image gathered, described ARM11 processor and described Defect Detection equipment connection, for determining based on described flaw information whether corresponding capsule is flaw capsule.
More specifically, in described capsule near infrared defect analyses system, also comprise: capsule transmission entrance, is arranged on capsule transport sector front, for by each capsule by being pushed to capsule transport sector, capsule transport sector, for transmitting each capsule one by one, static storage device, for prestoring capsule gray threshold scope, all value is between 0-255 for all flaw gray thresholds in described capsule gray threshold scope, and described static storage device is also for prestoring presetted pixel amount threshold and predetermined number threshold value, described near infrared data acquisition equipment is arranged on capsule transport sector front upper, comprise black and white camera and near-infrared light source, near-infrared light source is for carrying out near-infrared transmission to every capsule on capsule transport sector, and black and white camera carries out imaging to obtain near-infrared image to the capsule of near-infrared transmission, described Defect Detection equipment is connected respectively with described black and white camera and described static storage device, for receiving described near-infrared image, described Defect Detection equipment comprises wavelet filtering subset, edge enhancer equipment, Threshold selection subset, Target Segmentation subset and feature extraction subset, described wavelet filtering subset is connected with described black and white camera, for performing the process of harr wavelet filtering to described near-infrared image, to obtain filtering image, described edge enhancer equipment is connected with described wavelet filtering subset, strengthens process, to obtain enhancing image for performing edge to filtering image, described Threshold selection subset is connected respectively with described static storage device and described edge enhancer equipment, for selecting a value as preliminary election gray threshold successively from described capsule gray threshold scope, adopt preliminary election gray threshold that enhancing image is divided into preliminary election background area and pre-selected target region, calculate preliminary election background area and occupy the area ratio of enhancing image as the first area ratio, calculate the pixel average gray value of preliminary election background area as the first average gray value, calculate pre-selected target region and occupy the area ratio of enhancing image as second area ratio, calculate the pixel average gray value in pre-selected target region as the second average gray value, first average gray value is deducted the second average gray value, the difference obtained square be multiplied by the first area ratio and second area ratio, the product obtained is as threshold value product, the preliminary election gray threshold selecting threshold value product maximum is as target gray threshold value, described Target Segmentation subset is connected with described Threshold selection subset, for adopting target gray threshold value, enhancing image is divided into background image and target image, described feature extraction subset is connected with described Target Segmentation subset, based on described target image extraction flaw subimage wherein, described ARM11 processor is connected respectively with described static storage device and described Defect Detection equipment, to receive described flaw subimage and described presetted pixel amount threshold, calculate the quantity of the pixel of pixel value non-zero in described flaw subimage, when the quantity of the pixel of non-zero is more than or equal to described presetted pixel amount threshold, send and there is flaw signal, otherwise, send and there is not flaw signal, rejecting mechanism, be connected with described ARM11 processor, comprise solenoid valve and actuating equipment, after described solenoid valve and described actuating equipment are all arranged on described near infrared data acquisition equipment, described solenoid valve receive that described ARM11 processor sends there is flaw signal time, drive described actuating equipment to reject flaw capsule, counter, is connected with described ARM11 processor, receive described ARM11 processor send there is flaw signal time, the count value of counter adds 1, power-supply unit, comprise solar powered device, commercial power interface, change-over switch and electric pressure converter, described change-over switch is connected respectively with described solar powered device and described commercial power interface, line voltage size according to commercial power interface place determines whether be switched to described solar powered device to be powered by described solar powered device, described electric pressure converter is connected with described change-over switch, with the 5V voltage transitions will inputted by change-over switch for 3.3V voltage, sound and light alarm equipment, is connected with described ARM11 processor, during for crossing multi signal at the flaw receiving the transmission of described ARM11 processor, carries out corresponding sound and light alarm operation, wherein, described ARM11 processor, when the count value of described counter is more than or equal to described predetermined number threshold value, sends flaw and crosses multi signal, when the count value of described counter is less than described predetermined number threshold value, sends flaw tolerable signal.
More specifically, in described capsule near infrared defect analyses system, described analytic system also comprises: display device, be connected with described ARM11 processor, for receiving and showing the count value of counter that described ARM11 processor sends and flaw crosses multi signal, also for receiving the rejecting number of times of the determined described actuating equipment of described rejecting mechanism.
More specifically, in described capsule near infrared defect analyses system: described display device is LCDs.
More specifically, in described capsule near infrared defect analyses system: described wavelet filtering subset, described edge enhancer equipment, described Threshold selection subset, described Target Segmentation subset and described feature extraction subset adopt different fpga chips to realize respectively.
More specifically, in described capsule near infrared defect analyses system: described wavelet filtering subset, described edge enhancer equipment, described Threshold selection subset, described Target Segmentation subset and described feature extraction subset are integrated on one piece of surface-mounted integrated circuit.
Accompanying drawing explanation
Below with reference to accompanying drawing, embodiment of the present invention are described, wherein:
Fig. 1 is the block diagram of the capsule near infrared defect analyses system illustrated according to an embodiment of the present invention.
Reference numeral: 1 near infrared data acquisition equipment; 2 Defect Detection equipment; 3ARM11 processor
Embodiment
Below with reference to accompanying drawings the embodiment of capsule near infrared defect analyses system of the present invention is described in detail.
Current capsule detects the general means adopting graphical analysis, and first cut from background punishment by capsule, extract unwanted visual characteristic from capsule subsequently, whether the unwanted visual characteristic determination capsule based on capsule exists flaw.But lack effective segmentation threshold and unwanted visual characteristic in prior art, the precision causing capsule to detect is a greater impact.
In order to overcome above-mentioned deficiency, the present invention has built a kind of capsule near infrared defect analyses system, adopt the capsule connecting gear of near infrared detecting pattern, streamline, automatic reject mechanism and adaptive segmentation threshold, simultaneously, whether the pixel count determination capsule based on flaw image exists flaw, thus effectively solves the problem.
Fig. 1 is the block diagram of the capsule near infrared defect analyses system illustrated according to an embodiment of the present invention, described analytic system comprises near infrared data acquisition equipment, Defect Detection equipment and ARM11 processor, described near infrared data acquisition equipment is used for carrying out near-infrared image collection to every capsule, described Defect Detection equipment is connected with described near infrared data acquisition equipment, for extracting the flaw information of corresponding capsule based on the near-infrared image gathered, described ARM11 processor and described Defect Detection equipment connection, for determining based on described flaw information whether corresponding capsule is flaw capsule.
Then, continue to be further detailed the concrete structure of capsule near infrared defect analyses system of the present invention.
Described analytic system also comprises: capsule transmission entrance, is arranged on capsule transport sector front, for by each capsule by being pushed to capsule transport sector.
Described analytic system also comprises: capsule transport sector, for transmitting each capsule one by one.
Described analytic system also comprises: static storage device, for prestoring capsule gray threshold scope, all value is between 0-255 for all flaw gray thresholds in described capsule gray threshold scope, and described static storage device is also for prestoring presetted pixel amount threshold and predetermined number threshold value.
Described near infrared data acquisition equipment is arranged on capsule transport sector front upper, comprise black and white camera and near-infrared light source, near-infrared light source is for carrying out near-infrared transmission to every capsule on capsule transport sector, and black and white camera carries out imaging to obtain near-infrared image to the capsule of near-infrared transmission.
Described Defect Detection equipment is connected respectively with described black and white camera and described static storage device, for receiving described near-infrared image; Described Defect Detection equipment comprises wavelet filtering subset, edge enhancer equipment, Threshold selection subset, Target Segmentation subset and feature extraction subset.
Described wavelet filtering subset is connected with described black and white camera, for performing the process of harr wavelet filtering to described near-infrared image, to obtain filtering image; Described edge enhancer equipment is connected with described wavelet filtering subset, strengthens process, to obtain enhancing image for performing edge to filtering image.
Described Threshold selection subset is connected respectively with described static storage device and described edge enhancer equipment, for selecting a value as preliminary election gray threshold successively from described capsule gray threshold scope, adopt preliminary election gray threshold that enhancing image is divided into preliminary election background area and pre-selected target region, calculate preliminary election background area and occupy the area ratio of enhancing image as the first area ratio, calculate the pixel average gray value of preliminary election background area as the first average gray value, calculate pre-selected target region and occupy the area ratio of enhancing image as second area ratio, calculate the pixel average gray value in pre-selected target region as the second average gray value, first average gray value is deducted the second average gray value, the difference obtained square be multiplied by the first area ratio and second area ratio, the product obtained is as threshold value product, the preliminary election gray threshold selecting threshold value product maximum is as target gray threshold value.
Described Target Segmentation subset is connected with described Threshold selection subset, for adopting target gray threshold value, enhancing image is divided into background image and target image; Described feature extraction subset is connected with described Target Segmentation subset, based on described target image extraction flaw subimage wherein.
Described ARM11 processor is connected respectively with described static storage device and described Defect Detection equipment, to receive described flaw subimage and described presetted pixel amount threshold, calculate the quantity of the pixel of pixel value non-zero in described flaw subimage, when the quantity of the pixel of non-zero is more than or equal to described presetted pixel amount threshold, send and there is flaw signal, otherwise, send and there is not flaw signal.
Described analytic system also comprises: rejecting mechanism, be connected with described ARM11 processor, comprise solenoid valve and actuating equipment, after described solenoid valve and described actuating equipment are all arranged on described near infrared data acquisition equipment, described solenoid valve receive that described ARM11 processor sends there is flaw signal time, drive described actuating equipment to reject flaw capsule.
Described analytic system also comprises: counter, is connected with described ARM11 processor, receive described ARM11 processor send there is flaw signal time, the count value of counter adds 1.
Described analytic system also comprises: power-supply unit, comprise solar powered device, commercial power interface, change-over switch and electric pressure converter, described change-over switch is connected respectively with described solar powered device and described commercial power interface, line voltage size according to commercial power interface place determines whether be switched to described solar powered device to be powered by described solar powered device, described electric pressure converter is connected with described change-over switch, with the 5V voltage transitions will inputted by change-over switch for 3.3V voltage.
Described analytic system also comprises: sound and light alarm equipment, is connected with described ARM11 processor, during for crossing multi signal at the flaw receiving the transmission of described ARM11 processor, carries out corresponding sound and light alarm operation.
Wherein, described ARM11 processor, when the count value of described counter is more than or equal to described predetermined number threshold value, sends flaw and crosses multi signal, when the count value of described counter is less than described predetermined number threshold value, sends flaw tolerable signal.
Alternatively, in described capsule near infrared defect analyses system, described analytic system also comprises: display device, be connected with described ARM11 processor, for receiving and showing the count value of counter that described ARM11 processor sends and flaw crosses multi signal, also for receiving the rejecting number of times of the determined described actuating equipment of described rejecting mechanism; Described display device is LCDs; Described wavelet filtering subset, described edge enhancer equipment, described Threshold selection subset, described Target Segmentation subset and described feature extraction subset adopt different fpga chips to realize respectively; And, described wavelet filtering subset, described edge enhancer equipment, described Threshold selection subset, described Target Segmentation subset and described feature extraction subset are integrated on one piece of surface-mounted integrated circuit.
In addition, FPGA (Field-ProgrammableGateArray), i.e. field programmable gate array, he is the product further developed on the basis of the programming devices such as PAL, GAL, CPLD.He occurs as a kind of semi-custom circuit in special IC (ASIC) field, has both solved the deficiency of custom circuit, overcomes again the shortcoming that original programming device gate circuit number is limited.
With the circuit design that hardware description language (Verilog or VHDL) completes, can through simple comprehensive and layout, being burned onto fast on FPGA and testing, is the technology main flow of modern IC designs checking.These can be edited element and can be used to realize some basic logic gates (such as AND, OR, XOR, NOT) or more more complex combination function such as demoder or mathematical equation.Inside most FPGA, in these editable elements, also comprise memory cell such as trigger (Flip-flop) or other more complete block of memory.System designer can be coupled together the logical block of FPGA inside by editable connection as required, just looks like that a breadboard has been placed in a chip.One dispatch from the factory after the logical block of finished product FPGA can change according to deviser with being connected, so FPGA can complete required logic function.
FPGA is in general slow than the speed of ASIC (special IC), realizes same function ratio ASIC circuit area and wants large.But they also have a lot of advantages such as can finished product fast, can be modified the mistake in correction program and more cheap cost.Manufacturer also may provide the FPGA of cheap still edit capability difference.Because these chips have poor can edit capability, so exploitations of these designs complete on common FPGA, then design is transferred to one and is similar on the chip of ASIC.Another method is with CPLD (ComplexProgrammableLogicDevice, CPLD).The exploitation of FPGA has a great difference relative to the exploitation of conventional P C, single-chip microcomputer.FPGA, based on concurrent operation, realizes with hardware description language; Very large difference is had compared to the sequential operation of PC or single-chip microcomputer (no matter being von Neumann structure or Harvard structure).
As far back as 1980 mid-nineties 90s, FPGA takes root in PLD equipment.CPLD and FPGA includes the Programmadle logic unit of some relatively large amount.The density of CPLD logic gate is between several thousand to several ten thousand logical blocks, and FPGA normally arrives millions of several ten thousand.The key distinction of CPLD and FPGA is their system architecture.CPLD is a somewhat restrictive structure.This structure is arranged by the logical groups of one or more editable result sum and forms with the register of the locking of some relatively small amounts.Such result lacks editor's dirigibility, but but have the time delay and logical block that can estimate to the advantage of linkage unit height ratio.And FPGA has a lot of linkage units, although allow him edit more flexibly like this, structure is complicated many.
Adopt capsule near infrared defect analyses system of the present invention, for in prior art the identification of capsule flaw difficulty, reject inefficient technical matters, based on the profile nature of capsule and capsule flaw, introduce various image processing equipment targetedly, adopt pipelining mode and automatic reject mechanism simultaneously, efficiently solve above-mentioned technical matters.
Be understandable that, although the present invention with preferred embodiment disclose as above, but above-described embodiment and be not used to limit the present invention.For any those of ordinary skill in the art, do not departing under technical solution of the present invention ambit, the technology contents of above-mentioned announcement all can be utilized to make many possible variations and modification to technical solution of the present invention, or be revised as the Equivalent embodiments of equivalent variations.Therefore, every content not departing from technical solution of the present invention, according to technical spirit of the present invention to any simple modification made for any of the above embodiments, equivalent variations and modification, all still belongs in the scope of technical solution of the present invention protection.

Claims (6)

1. a capsule near infrared defect analyses system, described analytic system comprises near infrared data acquisition equipment, Defect Detection equipment and ARM11 processor, described near infrared data acquisition equipment is used for carrying out near-infrared image collection to every capsule, described Defect Detection equipment is connected with described near infrared data acquisition equipment, for extracting the flaw information of corresponding capsule based on the near-infrared image gathered, described ARM11 processor and described Defect Detection equipment connection, for determining based on described flaw information whether corresponding capsule is flaw capsule.
2. capsule near infrared defect analyses system as claimed in claim 1, it is characterized in that, described analytic system also comprises:
Capsule transmission entrance, is arranged on capsule transport sector front, for by each capsule by being pushed to capsule transport sector;
Capsule transport sector, for transmitting each capsule one by one;
Static storage device, for prestoring capsule gray threshold scope, all value is between 0-255 for all flaw gray thresholds in described capsule gray threshold scope, and described static storage device is also for prestoring presetted pixel amount threshold and predetermined number threshold value;
Described near infrared data acquisition equipment is arranged on capsule transport sector front upper, comprise black and white camera and near-infrared light source, near-infrared light source is for carrying out near-infrared transmission to every capsule on capsule transport sector, and black and white camera carries out imaging to obtain near-infrared image to the capsule of near-infrared transmission;
Described Defect Detection equipment is connected respectively with described black and white camera and described static storage device, for receiving described near-infrared image, described Defect Detection equipment comprises wavelet filtering subset, edge enhancer equipment, Threshold selection subset, Target Segmentation subset and feature extraction subset, described wavelet filtering subset is connected with described black and white camera, for performing the process of harr wavelet filtering to described near-infrared image, to obtain filtering image, described edge enhancer equipment is connected with described wavelet filtering subset, strengthens process, to obtain enhancing image for performing edge to filtering image, described Threshold selection subset is connected respectively with described static storage device and described edge enhancer equipment, for selecting a value as preliminary election gray threshold successively from described capsule gray threshold scope, adopt preliminary election gray threshold that enhancing image is divided into preliminary election background area and pre-selected target region, calculate preliminary election background area and occupy the area ratio of enhancing image as the first area ratio, calculate the pixel average gray value of preliminary election background area as the first average gray value, calculate pre-selected target region and occupy the area ratio of enhancing image as second area ratio, calculate the pixel average gray value in pre-selected target region as the second average gray value, first average gray value is deducted the second average gray value, the difference obtained square be multiplied by the first area ratio and second area ratio, the product obtained is as threshold value product, the preliminary election gray threshold selecting threshold value product maximum is as target gray threshold value, described Target Segmentation subset is connected with described Threshold selection subset, for adopting target gray threshold value, enhancing image is divided into background image and target image, described feature extraction subset is connected with described Target Segmentation subset, based on described target image extraction flaw subimage wherein,
Described ARM11 processor is connected respectively with described static storage device and described Defect Detection equipment, to receive described flaw subimage and described presetted pixel amount threshold, calculate the quantity of the pixel of pixel value non-zero in described flaw subimage, when the quantity of the pixel of non-zero is more than or equal to described presetted pixel amount threshold, send and there is flaw signal, otherwise, send and there is not flaw signal;
Rejecting mechanism, be connected with described ARM11 processor, comprise solenoid valve and actuating equipment, after described solenoid valve and described actuating equipment are all arranged on described near infrared data acquisition equipment, described solenoid valve receive that described ARM11 processor sends there is flaw signal time, drive described actuating equipment to reject flaw capsule;
Counter, is connected with described ARM11 processor, receive described ARM11 processor send there is flaw signal time, the count value of counter adds 1;
Power-supply unit, comprise solar powered device, commercial power interface, change-over switch and electric pressure converter, described change-over switch is connected respectively with described solar powered device and described commercial power interface, line voltage size according to commercial power interface place determines whether be switched to described solar powered device to be powered by described solar powered device, described electric pressure converter is connected with described change-over switch, with the 5V voltage transitions will inputted by change-over switch for 3.3V voltage;
Sound and light alarm equipment, is connected with described ARM11 processor, during for crossing multi signal at the flaw receiving the transmission of described ARM11 processor, carries out corresponding sound and light alarm operation;
Wherein, described ARM11 processor, when the count value of described counter is more than or equal to described predetermined number threshold value, sends flaw and crosses multi signal, when the count value of described counter is less than described predetermined number threshold value, sends flaw tolerable signal.
3. capsule near infrared defect analyses system as claimed in claim 2, it is characterized in that, described analytic system also comprises:
Display device, is connected with described ARM11 processor, for receiving and showing the count value of counter that described ARM11 processor sends and flaw crosses multi signal, also for receiving the rejecting number of times of the determined described actuating equipment of described rejecting mechanism.
4. capsule near infrared defect analyses system as claimed in claim 2, is characterized in that:
Described display device is LCDs.
5. capsule near infrared defect analyses system as claimed in claim 2, is characterized in that:
Described wavelet filtering subset, described edge enhancer equipment, described Threshold selection subset, described Target Segmentation subset and described feature extraction subset adopt different fpga chips to realize respectively.
6. the capsule near infrared defect analyses system as described in as arbitrary in claim 2-5, is characterized in that:
Described wavelet filtering subset, described edge enhancer equipment, described Threshold selection subset, described Target Segmentation subset and described feature extraction subset are integrated on one piece of surface-mounted integrated circuit.
CN201510535359.3A 2015-08-27 2015-08-27 Near-infrared defect analyzing system for capsules Pending CN105136733A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510535359.3A CN105136733A (en) 2015-08-27 2015-08-27 Near-infrared defect analyzing system for capsules

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510535359.3A CN105136733A (en) 2015-08-27 2015-08-27 Near-infrared defect analyzing system for capsules

Publications (1)

Publication Number Publication Date
CN105136733A true CN105136733A (en) 2015-12-09

Family

ID=54722160

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510535359.3A Pending CN105136733A (en) 2015-08-27 2015-08-27 Near-infrared defect analyzing system for capsules

Country Status (1)

Country Link
CN (1) CN105136733A (en)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101788469A (en) * 2010-03-08 2010-07-28 辅仁药业集团有限公司 Method for online detecting near infrared spectrum of active ingredients of compound eucommia bark capsules
EP1664749B1 (en) * 2003-09-24 2010-09-29 3M Innovative Properties Company Apparatus and method for automated web inspection

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1664749B1 (en) * 2003-09-24 2010-09-29 3M Innovative Properties Company Apparatus and method for automated web inspection
CN101788469A (en) * 2010-03-08 2010-07-28 辅仁药业集团有限公司 Method for online detecting near infrared spectrum of active ingredients of compound eucommia bark capsules

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
彭真明 等: "《光电图像处理及应用》", 30 April 2013 *
李杰: "基于图像分析的胶囊缺陷检测系统研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *
王娟: "基于红外图像的胶囊缺陷检测研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *

Similar Documents

Publication Publication Date Title
CN105184783A (en) Glass defect type identification system
CN105092593A (en) Steel plate defect detection method based on high-intensity illumination
CN103198705B (en) Parking place state automatic detection method
CN101504716A (en) QR two-dimension bar code recognition method and system based on field programmable gate array
CN104913797A (en) Pointer type instrument number reading and recognition method and system
CN105181708A (en) Qualification detection platform of sewing needles in batches
CN105160670A (en) Glass defect type identification method
CN106483130B (en) A kind of detection method and its automatic detection device of rice disease
CN105044119A (en) Glass flaw classification method based on gray mean value analysis
CN114723709A (en) Tunnel disease detection method and device and electronic equipment
CN104952247A (en) Congestion level analysis platform based on double communication data
CN110619619A (en) Defect detection method and device and electronic equipment
CN115605746A (en) Inspection device, cell selection device, inspection method, and inspection program
CN104835329B (en) Based on the section congestion level detection system of remote sensing communication
CN104836597A (en) Prison monitoring method based on power line communication
CN105139400A (en) Workpiece defect positioning system based on image processing
CN105136734A (en) Capsule near-infrared fault analysis method
CN105181705A (en) Ceramic appearance analysis method based on multiple-filter
CN105136810A (en) Steel plate defect detecting platform based on high-strength lighting
CN105096325A (en) Underwater equipment detection system based on laser image
CN105136817A (en) Capsule visible light defect recognition method based on wireless network
CN105136733A (en) Near-infrared defect analyzing system for capsules
CN105160671A (en) Capsule visible light defect identification apparatus based on wireless network
CN111931721A (en) Method and device for detecting color and number of annual inspection label and electronic equipment
CN105241891A (en) Glass defect detection method based on WIFI network

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right

Effective date of registration: 20170424

Address after: 271104 Shandong Province, Laiwu City Gangcheng District Front Street No. 9

Applicant after: Li Xiying

Address before: 271104 Shandong Province, Laiwu City Gangcheng District Front Street No. 9

Applicant before: Li Xuexin

TA01 Transfer of patent application right
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20151209

WD01 Invention patent application deemed withdrawn after publication