Weirong JBYD-N9(A) currency counting machine | Yunnan Class A currency counting machine |

& 1. Product introduction:
c=r: Weirong

Counter currency detector& takes the theory of authentic and counterfeit&r as the guiding ideology of project design, and uses multi-spectrum extracted from real coins based on reality The image characteristic signal is designed as a basis for judging counterfeit currency. The anti-counterfeiting discrimination rate for the latest super counterfeit currency and spliced (altered) currency currently circulating in the market can reach
%
. The specific technical means are as follows:
c=r: >White light image identification:
Using red, green and blue

Three primary color light source reflection type
C
Image sensor, resolution in

Carry out banknote scanning, imaging, collection, analysis, and processing to realize the authenticity identification of banknote image features.
c=r: >UV image identification:
Use of purple light

Reflective light source
C
Image sensor, resolution
< br/> Carry out banknote scanning, imaging, collection, analysis, and processing to realize the authenticity identification of banknote fluorescent ink image features.
c=r: >Infrared image identification:
Using infrared

Emitting light source reflection
C
Image sensor, resolution in
< br/> Carry out scanning, imaging, collection, analysis and processing of banknotes to realize the authenticity identification of the infrared ink image features of banknotes.
c=r: >Ultraviolet optical characteristic analysis and identification:
Use specific wavelength violet light-emitting diodes (wavelength
)
to characterize the paper or printing ink of banknotes under luminous excitation. By amplifying the received signal, the microprocessor performs spectral characteristic analysis to identify authenticity.
c=r: >White light image identification:
Using infrared light source, purple light source, and red, green, blue

Three primary color light source reflection type
C
Image sensor with a resolution of

Scans the banknotes and collects and analyzes the images to realize the authenticity identification of various image features of the banknotes.
c=r: Identification of infrared optical characteristics:
Use infrared rays of a specific wavelength to linearly scan the face of the ticket, analyze the spectral curve of the paper's response to infrared characteristics, and analyze the spectral characteristics and spectral curves through a microprocessor. Identify authenticity.
c=r: Fluorescence feature identification:
Specific wavelength ultraviolet light-emitting diodes are used to emit colored fluorescent ink and invisible special fluorescent ink for banknotes, and optical sensors are equipped with filter lenses of different wavelengths for reception. Process and analyze spectral characteristics to identify authenticity.
c=r: Magnetic ink feature identification:
Use multiple sets of magnetic heads to measure the magnetic ink at different positions of the banknotes, and use quantitative fixed-point qualitative analysis to analyze various data such as the amplitude spectrum of the magnetic signal to analyze and identify the authenticity. Fake.
c=r: >Safety line feature analysis and identification:
Using high-sensitivity inductive magnetic sensors and low-noise integrated operational amplifier circuits, automatically performed by a microprocessor

Convert, read the magnetic encoding information of the security thread, analyze and determine the denomination and authenticity of the banknotes. At present, this method can effectively deal with simulated security thread counterfeit currency. Our company has the patented technology for this invention.
c=r: >Serial number recognition:
The banknotes pass
C
The image sensor scans and analyzes the banknotes to extract the image features of the serial number for identification and recording

Disk or
C
Storage can be compared and filtered with the preset serial number and can provide alarm prompts to avoid the circulation of counterfeit coins with the same number.
c=r: >Banknote area recognition:
The banknote is scanned through the code plate sensor and
C
image sensor, and the banknote is quickly calculated through data analysis by the processor to identify the banknote. The area and the defective area of the banknote can reliably identify the denomination and defective function of the banknote (cracks, holes, folded corners, half sheets and continuous sheets, etc.).
c=r: Adhesive paper detection:
Through infrared rays to stimulate the spectral characteristics of paper, and through signal amplification and transmission to a microprocessor for analysis and judgment, the adhesive paper attached to banknotes can be reliably identified. Banknotes are fed in from the banknote inlet. During the transmission channel, they pass through the image identification device, the magnetic identification device, and the infrared and purple light identification devices in sequence. The image identification device uses wavelength classification to collect and process, analyze with software algorithms, and process counterfeit currency and other technical processing steps, including various related combinations such as infrared and magnetic combination, magnetic and image combination, infrared and image, and purple light. The fuzzy algorithm is used to finally determine whether the banknotes counted are counterfeit. The fuzzy algorithm can greatly improve the ability to detect counterfeiting and ensure the safety of currency circulation.