Palmvein Recognition SDK - Server

This stands for palm-vein reader, palmvein scanner, palmvein recognition, palmvein matching, hand landmark, palmvein identity, palmvein comparison on Linux and Windows

We provide customers with the Palmvein Recognition SDK for both Windows and Linux.

Features

• Hand Landmark Extraction

• Hand Detection

• Palmvein ROI extraction(alignment)

• Palmvein Feature Extraction

• Palmvein Feature Comparison, Matching

• Gradio Demo For Checking API

License

We offer lifetime license(perpetual license) based on machine ID for every server(Windows, Linux). The license is available for one-time payment. In other words, once you purchase license from me, you can use our SDK permanently.

To request a license, please contact us:

Email: [e-mail]

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System Requirements

1. Linux

• CPU: 2 cores or more (Recommended: 2 cores)

• RAM: 4 GB or more (Recommended: 8 GB)

• HDD: 4 GB or more (Recommended: 8 GB)

• OS: Windows 7 or later

• Architecture: x64

2. Windows

• CPU: 2 cores or more (Recommended: 2 cores)

• RAM: 4 GB or more (Recommended: 8 GB)

• HDD: 4 GB or more (Recommended: 8 GB)

• OS: Ubuntu 20.04 or later

• Architecture: x64

Initializing SDK

• Obtain macihne code to activate and request license.

# Python code example
machineCode = getMachineCode()
print("\nmachineCode: ", machineCode.decode('utf-8'))

• Activate SDK using licnese key

# Python code example
ret = setActivation(license.encode('utf-8'))
print("\nactivation: ", ret)

• Once ret value is zero, SDK can get work started.

APIs

ROI Extraction The SDK provides a single API for detecting hands and extracting ROI from the whole hand image(palmvein). The function can be used as follows:

# Python code example
roi, label = get_roi_image(cv2.flip(image, 1))

Next, Create Feature getFeature function returns palmvein feature against ROI data.

# Python code example
cnt = getFeature(roi_byte, len(roi_byte), feature_array)

1. ROI Extraction

ROI Extraction The SDK provides a single API for detecting hands and extracting ROI from the whole hand image(palmvein). The function can be used as follows.

# Python code example
roi, label = get_roi_image(cv2.flip(image, 1))

• image: input image

• label: Left hand or Right one

• roi: hand ROI(Region Of Interest) image to get palm feature.

2. Feature Extraction

Create Feature getFeature function returns palmvein feature against ROI data.

The function can be used as follows:

# Python code example
cnt = getFeature(roi_byte, len(roi_byte), feature_array)

• roi_byte: ROI image in byte format (image should be converted to byte format by function mat_to_byets()).

• feature_array: palmvein feature extracted from hand ROI data.

3. Similarity Evaluation

The getScore() function takes two palmvein features as arguments and returns score value to determine whether 2 input hands are from the same or different.

# Python code example
score = getScore(feature_array1, cnt1, feature_array2, cnt2)