@li0ard/tsemrtd/dist/dg3.js

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

import { TLV } from "@li0ard/tinytlv";
import { Enums, Interfaces, Schemas, Utils } from "./index";
import { AsnConvert } from "@peculiar/asn1-schema";
/**
 * Class for working with DG3 (Fingerprint)
 * @hideconstructor
*/
export class DG3 {
    /**
     * 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];
        }
        else if (end - start == 4) {
            return (data[start] << 24) | (data[start + 1] << 16) | (data[start + 2] << 8) | data[start + 3];
        }
        return parseInt(Utils.bytesToHex(data.slice(start, end)), 16);
    }
    /**
     * 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) != 0x46495200)
            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 + 6);
        offset += 6;
        let captureDeviceId = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let acquisitionLevel = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let count = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let scaleUnits = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let scanResolutionHorizontal = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let scanResolutionVertical = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let imageResolutionHorizontal = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let imageResolutionVertical = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let depth = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let imageType = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let reserved = this.extractContent(data, offset, offset + 2);
        offset += 2;
        let fingerprintRecordLength = this.extractContent(data, offset, offset + 4);
        offset += 4;
        let fingerType = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let lengthOfRepresentations = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let nrOfRepresention = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let quality = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let fingerImageType = 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 reserved2 = this.extractContent(data, offset, offset + 1);
        offset += 1;
        let imageEnd = fingerprintRecordLength - 14;
        let imageData = data.subarray(offset, offset + imageEnd);
        return {
            sbh,
            lengthOfRecord,
            captureDeviceId,
            acquisitionLevel,
            count,
            scaleUnits,
            scanResolutionHorizontal,
            scanResolutionVertical,
            imageResolutionHorizontal,
            imageResolutionVertical,
            depth,
            fingerprintRecordLength,
            fingerImageType,
            lengthOfRepresentations,
            nrOfRepresention,
            quality,
            fingerType,
            imageType,
            imageWidth,
            imageHeight,
            imageData
        };
    }
    /**
     * Get image of fingerprint and meta info
     * @param data Data of EF.DG3 file
     */
    static load(data) {
        let tlv = TLV.parse(data);
        if (parseInt(tlv.tag, 16) != Enums.TAGS.DG3)
            throw new Error(`Invalid DG3 tag "0x${tlv.tag}", expected 0x${Enums.TAGS.DG3.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 DG3().readBDB(bigt.childs[i + 1]));
        }
        return results;
    }
}