vennsa/SLR-NoteSense

SLR-NoteSense

SLR-NoteSense is a dual-sensor RGBC dataset for Sri Lankan banknote denomination recognition.

The dataset contains 12,668 paired sensor measurements collected from 634 distinct physical Sri Lankan banknotes across six denominations:

• —LKR 20
• —LKR 50
• —LKR 100
• —LKR 500
• —LKR 1000
• —LKR 5000

Dataset Details

Two TCS34725 color sensors were used to collect red, green, blue, and clear-channel measurements.

Sensor settings:

• —Integration time: 50 ms
• —Gain: 4X
• —Number of sensors: 2
• —Number of physical banknotes: 634
• —Raw measurements: 12,668
• —Stable measurements after preprocessing: 12,035

Dataset Structure

Each row contains:

• —label
• —note_id
• —scan_id
• —sample_index
• —s1_r
• —s1_g
• —s1_b
• —s1_clear
• —s1_nr
• —s1_ng
• —s1_nb
• —s2_r
• —s2_g
• —s2_b
• —s2_clear
• —s2_nr
• —s2_ng
• —s2_nb

Normalized channels are calculated as:

R/C, G/C, and B/C.

Physical Banknote Distribution

Preprocessing

The first sensor reading of each acquisition sequence showed a sensor-settling transient and was excluded from the stable dataset.

A total of 60 missing denomination labels were restored from denomination-specific source files.

For machine-learning evaluation, all measurements from the same physical banknote should remain in the same train, validation, or test partition.

Use denomination + note_id as the physical-banknote group identifier.

Baseline Validation

An RBF Support Vector Machine using eight scan-level features achieved:

• —Group-aware repeated cross-validation accuracy: 98.33%
• —Macro F1-score: 98.33%
• —Group-held-out accuracy: 96.85%
• —Python-to-C++ prediction agreement: 634/634

These results are provided as technical validation of the dataset.

Intended Uses

This dataset is intended for research in:

• —banknote denomination recognition
• —embedded machine learning
• —color-sensor classification
• —assistive technology
• —feature engineering
• —group-aware machine-learning evaluation

Out-of-Scope Uses

The dataset is not intended for:

• —counterfeit detection
• —banknote authentication
• —financial security verification
• —banknote valuation

License

This dataset is released under the Creative Commons Attribution 4.0 International license.

Citation

Citation information will be added after publication of the associated data paper.

Dataset Version

Version 1.0