@li0ard/tsemrtd/dist/dg2.js

simple library for eMRTD. supports browsers, node, bun and more!

import { TLV } from "@li0ard/tinytlv";
import { Enums, Interfaces, Schemas } from "./index";
import { AsnConvert } from "@peculiar/asn1-schema";
/**
 * Class for working with DG2 (Face)
*/
export class DG2 {
    /**
     * Extract int from Uint8Array
     * @param data Uint8Array
     * @param start Offset
     * @param end Offset+length
     */
    extractContent(data, start, end) {
        if (end - start === 1) {
            return data[start];
        }
        else if (end - start < 4) {
            return (data[start] << 8) | data[start + 1];
        }
        return (data[start] << 24) | (data[start + 1] << 16) | (data[start + 2] << 8) | data[start + 3];
    }
    /**
     * Read Biometric data block
     * @hidden
     * @param tlv
     */
    readBDB(tlv) {
        if (parseInt(tlv.tag, 16) != 0x7f60)
            throw new Error(`Invalid object tag "0x${tlv.tag}", expected 0x7f60`);
        let sbh = AsnConvert.parse(tlv.childs[0].toBytes(), Schemas.SBH);
        let firstBlock = tlv.childs[1];
        if (parseInt(firstBlock.tag, 16) != 0x5f2e && parseInt(firstBlock.tag, 16) != 0x7f2e)
            throw new Error(`Invalid object tag "0x${tlv.tag}", expected 0x5f2e or 0x7f2e`);
        let data = firstBlock.byteValue;
        if (this.extractContent(data, 0, 4) != 0x46414300)
            throw new Error("Biometric data block is invalid");
        let offset = 4;
        if (this.extractContent(data, offset, offset + 4) != 0x30313000)
            throw new Error("Version of Biometric data is not valid");
        offset += 4;
        let lengthOfRecord = this.extractContent(data, offset, offset + 4);
        offset += 4;
        let numberOfFacialImages = this.extractContent(data, offset, offset + 2);
        offset += 2;
        if (numberOfFacialImages > 1)
            console.warn("[DG2] The record contains more than 1 image.");
        let facialRecordDataLength = this.extractContent(data, offset, offset + 4);
        offset += 4;
        let nrFeaturePoints = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let gender = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let eyeColor = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let hairColor = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let featureMask = this.extractContent(data, offset, offset + 3);
        offset += 3;
        let expression = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let poseAngle = this.extractContent(data, offset, offset + 3);
        offset += 3;
        let poseAngleUncertainty = this.extractContent(data, offset, offset + 3);
        offset += 3;
        offset += nrFeaturePoints * 8;
        let faceImageType = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let _imageDataType = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let imageWidth = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let imageHeight = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let imageColorSpace = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let sourceType = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let deviceType = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let quality = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let imageEnd = facialRecordDataLength - 20 - (nrFeaturePoints * 8) - 12;
        let imageData = data.subarray(offset, offset + imageEnd);
        return {
            sbh,
            lengthOfRecord,
            numberOfFacialImages,
            facialRecordDataLength,
            nrFeaturePoints,
            gender,
            eyeColor,
            hairColor,
            featureMask,
            expression,
            poseAngle,
            poseAngleUncertainty,
            faceImageType,
            imageType: _imageDataType,
            imageWidth,
            imageHeight,
            imageColorSpace,
            sourceType,
            deviceType,
            quality,
            imageData
        };
    }
    /**
     * Get image of face and meta info
     * @param data Data of EF.DG2 file
     */
    static load(data) {
        let tlv = TLV.parse(data);
        if (parseInt(tlv.tag, 16) != Enums.TAGS.DG2)
            throw new Error(`Invalid DG2 tag "0x${tlv.tag}", expected 0x${Enums.TAGS.DG2.toString(16)}`);
        let bigt = tlv.childs[0];
        if (parseInt(bigt.tag, 16) != 0x7f61)
            throw new Error(`Invalid object tag "0x${bigt.tag}", expected 0x7f61`);
        let bict = bigt.childs[0];
        if (parseInt(bict.tag, 16) != 0x02)
            throw new Error(`Invalid object tag "0x${bict.tag}", expected 0x02`);
        let bitCount = parseInt(bigt.childs[0].value, 16);
        let results = [];
        for (let i = 0; i < bitCount; i++) {
            results.push(new DG2().readBDB(bigt.childs[i + 1]));
        }
        return results;
    }
}