Artikel 1:Apa sebabe rai luwih apik tinimbang sidik jari?
Praktis 100% akurasi: Kaping pirang-pirang wis kabukten manawa sistem bekas driji gagal nalika driji reged, lengo, teles utawa bruised. Buruh sing kerja ing sistem oiling ora bisa ndhaptar kehadiran kanthi sidik jari sing burem. Cut ing driji bali kasalahan. Asring frustasi kanggo nyoba rawuh kaping pirang-pirang.
Sing ora kasus karo rawuh pangenalan pasuryan. Wis dicoba, dites lan buktiaken sing praktis 100% akurat. Karyawan mung lumaku menyang lan rawuh dijupuk. Kerjane sanajan gaya rambut ganti nganggo kacamata, utawa umur karyawan.
Keamanan tanpa tutul: Karo covid-19, donya wis dadi saya weruh risiko sistem rawuh basis kontak. Ora ana sistem rawuh, liyane saka sistem rawuh id pasuryan kang pancen touchfree. Pangguna kudu mung nuduhake pasuryane. Sistem micu kanthi otomatis.
Sanajan jagad iki bebas covid, wong bakal eling saka nutul padha nggawe lan iku bakal apik kanggo nyedhiyani sistem higienis.
Wah pengalamane: Kanthi wektu rawuh Cut-mudhun kanggo kurang saka detik lan ora perlu tumindak saka pangguna-mburi, rawuh id pasuryan minangka sistem biometrik sing paling apik. Iku wows karyawan sing ora mbutuhake latihan lan seneng diadopsi langsung. Coba pikirake nalika sampeyan nyekel secangkir kopi ing tangan siji lan tas tangan ing tangan liyane nalika sampeyan kudu nindakake sidik jari.. Apa yen kita ngganti kanggo ngadhepi rawuh pangenalan. Simpen masalah sampeyan kanthi luwih gampang tinimbang mung ngadeg ing ngarep layar.

Artikel 2:Carane nindakake karya sistem rawuh pangenalan pasuryan?
Iki nyimpen pasuryan pangguna ing basis data piranti kanthi ukuran layar sing beda, ing kasus TOMMI, saka 4.3inch kanggo 13inch. Nalika karyawan ngadeg ing ngarepe layar, iku njupuk pasuryan lan nggawe comparison realtime karo gambar pasuryan disimpen. Yen cocog, jam mlebu utawa jam metu direkam ing piranti. Iku bisa nindakake liveness judagement marang foto utawa video ngapusi.

Artikel 3:Carane ora rawuh pasuryan menang liwat sistem biometrik liyane?
Akeh perusahaan wis nggunakake sistem rawuh wektu sidik jari, kang bisa dadi sulih apik kanggo sistem punching kertu. Ora ana sing sampurna ing babagan linuwih lan keamanan. Piranti rawuh wektu pangenalan pasuryan wis digunakake dening akeh perusahaan gedhe ing taun-taun pungkasan. Nanging akeh organisasi ukuran medium lan cilik isih nggarap teknologi lawas.
Apa kita kudu nganyarke menyang sistem kehadiran ID pasuryan? Luwih becik kita nindakake analisis objektif.

Artikel 4:Apa sing keuntungan saka Access Control rai pangenalan?
Salah sawijining tren paling cepet ing desain lan teknologi bangunan yaiku aplikasi pengalaman pangguna tanpa tutul. Kombinasi ekspansi kanthi cepet ing urip multi-tenant & papan kerja lan pandhemen Coronavirus nyebabake kabutuhan kanggo urip lan lingkungan kerja tanpa kontak.
· Ngapikake keamanan
Piranti Pangenalan Rai generasi paling anyar nyedhiyakake otentikasi sing akurat lan aman banget, yen dibandhingake karo cara akses tradisional kayata kode PIN utawa entri lawang keyfob.
· Cepet, manajemen ID pangguna sing trep lan adoh
Tambahan, njabut lan kontrol akun Panganggo iku gampang lan prasaja kanggo administrator sistem lan bisa kebak ngatur mbatalake.
Dene otentikasi liwat piranti fisik mbutuhake fob utawa kertu kanggo diserahake utawa dikirim (lan bali), ID pangguna anyar bisa digawe lan dipateni dening administrator sistem (kayata keamanan, HR utawa concierge personel) saka sembarang situs remot nggunakake platform manajemen basis maya, Ngartekno nyepetake proses kanggo ngirit wektu lan dhuwit.
· Ora ana piranti bukti asli sing dibutuhake
Akeh cara mlebu lawang lan identifikasi akses mbutuhake nggunakake piranti fisik kanggo keasliane – kayata keyfob, kertu RFID utawa smartphone. Apa pangguna lali utawa ilang 'piranti’ (utawa luwih elek – wis dicolong), banjur padha ora bisa ngakses bangunan.
Piranti sing otentikasi’ pangenalan pasuryan bakal tansah, mesthi, karo kowe!
· Integrasi karo platform liyane
Sistem kontrol akses pangenalan rai uga bisa digabungake karo platform logistik lan sistem liyane, kayata wektu & rawuh, sistem pembayaran otomatis utawa sistem manajemen bangunan, mbantu ngembangake lingkungan bangunan sing cerdas.
Artikel 5:Carane bakal sistem pangenalan rai & algoritma dianggo ing 2022?

Pasar teknologi pangenalan rai berkembang kanthi cepet. Saka bandara sing gumantung ing data biometrik kanggo layar penumpang internasional, penegak hukum gumantung ing kanggo nyekel kriminal, lan media sosial digunakake kanggo keasliane pangguna, teknologi pangenalan rai iku perlu saka jam.
Ing 2022, pasar pangenalan rai samesthine kanggo nggayuh $7.7 milyar, munggah saka $4 milyar ing 2017. Iki amarga pangenalan rai duwe macem-macem aplikasi komersial. Bisa digunakake kanggo macem-macem tujuan, kalebu ndjogo lan marketing.
Carane manungsa ngenali pasuryan?
Sistem pangenalan ing otak kita rumit. Nyatane, ilmuwan isih nyoba kanggo mangerteni. Apa sing bisa kita anggep yaiku neuron ing otak kita pisanan ngenali pasuryan ing adegan kasebut (saka awak manungsa menyang latar mburi), kita extract fitur rai, lan simpen ing basis data kita dhewe. Nggunakake memori kita minangka database, kita banjur bisa klasifikasi wong miturut fitur sing. Kita wis dilatih ing dataset gedhe tanpa wates lan jaringan saraf tanpa wates ekstensif.
Piranti lunak pangenalan rai ing mesin ditindakake kanthi cara sing padha. Pisanan, kita aplikasi algoritma deteksi rai kanggo ndeteksi pasuryan ing pemandangan, extract fitur rai saka pasuryan sing dideteksi, lan nggunakake algoritma kanggo nggolongake wong.
Kepiye cara kerja Sistem Pangenalan Wajah?

1Deteksi pasuryan
Deteksi pasuryan minangka versi khusus saka Deteksi Objek, ing ngendi mung ana siji obyek sing bisa dideteksi – Pasuryaning manungsa.
Kaya wektu komputasi lan pertukaran ruang ing Ilmu Komputer, ana trade-off antarane kacepetan inferensi lan akurasi ing algoritma Machine Learning uga. Ana akeh algoritma deteksi obyek ing kana, lan algoritma beda duwe kacepetan lan akurasi trade-off.
We evaluated different state-of-the-art object detection algorithms:
OpenCV (Haar-Cascade)
MTCNN
YoloV3 and Yolo-Tiny
SSD
BlazeFace
ShuffleNet and Faceboxes
To build a robust face detection system, we need an accurate and fast algorithm to run on a GPU as well as a mobile device in real-time.
Accuracy
In real-time inference on streaming video, people can have different poses, occlusions, and lighting effects on their face. It is important to precisely detect faces in various lighting conditions as well as poses.

Detecting faces in various poses and lighting conditions
OpenCV (Haar-Cascade)
We started with Haar-cascade implementation of OpenCV, which is an open-source image manipulation library in C.
Pros: Since this library is written in C language. It is very fast for inference in real-time systems.
Cons: The problem with this implementation was that it was unable to detect side faces and performed poorly in different poses and lighting conditions.
MTCNN
This algorithm is based on Deep Learning methods. It uses Deep Cascaded Convolutional Neural Networks for detecting faces.
Pros: It had better accuracy than the OpenCV Haar-Cascade method
Cons: Higher run time
YOLOV3
YOLO face detection (You look only once) is the state-of-the-art Deep Learning algorithm for object detection. It has many convolutional neural networks, forming a Deep CNN model. (Deep means the model architecture complexity is enormous).
The original Yolo model can detect 80 different object classes with high accuracy. We used this Yolo facial recognition model for detecting only one object – the face.
We trained this algorithm on WiderFace (image dataset containing 393,703 face labels) dataset.
Ana uga versi miniatur saka algoritma Yolo kanggo deteksi pasuryan sing kasedhiya, Yolo-Tiny. Yolo-Tiny mbutuhake wektu komputasi sing luwih sithik kanthi kompromi akurasie. Kita nglatih model Yolo-Tiny kanthi set data sing padha, nanging asil kothak wates ora konsisten.
Pros: akurat banget, tanpa cacad. Luwih cepet tinimbang MTCNN.
Cons: Amarga nduweni lapisan Jaringan Neural Deep kolosal, mbutuhake sumber daya komputasi luwih akeh. Mangkono, iku alon kanggo mbukak ing CPU utawa piranti seluler. Ing GPU, iku njupuk luwih VRAM amarga arsitektur gedhe.
SSD
SSD (Detektor Tembakan Tunggal) uga model jaringan syaraf konvolusional jero kaya YOLO.
Pros: Akurasi apik. Bisa ndeteksi ing macem-macem pose, iluminasi, lan occlusions. Kacepetan inferensi sing apik.
Cons: Inferior kanggo model YOLO. Sanajan kacepetan inferensi apik, nanging isih ora cukup kanggo mbukak CPU, GPU kurang-mburi, utawa piranti seluler.
BlazeFace
Kaya jenenge, iku algoritma deteksi pasuryan sing cepet banget dirilis dening Google. Iku nampa 128×128 input gambar dimensi. Wektu inferensi kasebut ana ing sub-milidetik. Algoritma iki dioptimalake kanggo digunakake ing pangenalan rai ing ponsel. Alasane cepet banget yaiku:
Iku model detektor pasuryan khusus, ora kaya YOLO lan SSD, kang Originally digawe kanggo ndeteksi nomer akeh kelas. Mangkono BlazeFace nduweni arsitektur Deep Convolutional Neural Network sing luwih cilik tinimbang YOLO lan SSD.
Iku nggunakake Depthwise Separable Convolution tinimbang lapisan Convolution standar, sing ndadékaké komputasi luwih sithik.
Pros: Kacepetan inferensi sing apik banget lan deteksi rai sing akurat.
Cons: Model iki dioptimalake kanggo ndeteksi gambar rai saka kamera ponsel, lan kanthi mangkono ngarepake manawa pasuryan kudu nutupi sebagian besar wilayah ing gambar kasebut. It doesn’t work well when the face size is small. So in the case of CCTV camera images, it doesn’t perform well.
Faceboxes
The latest face recognition algorithm we used is Faceboxes. Like BlazeFace, it is a Deep Convolutional Neural network with small architecture and designed just for one class – Pasuryaning manungsa. Its inference time is real-time fast on CPU. Its accuracy is comparable to Yolo for face detection. It can detect small and large faces in an image precisely.
Pros: Fast inference speed and good accuracy.
Cons: Evaluation is in progress.
2Feature extraction
After detecting faces in an image, we crop the faces and feed them to a Feature Extraction Algorithm, which creates face embedding- a multi-dimensional (mostly 128 or 512 dimensional) vector representing features of the face.
We used the FaceNet algorithm to create face-embeddings.
Vektor semat makili fitur rai saka pasuryan wong. Dadi nanem vektor saka rong gambar sing beda saka wong sing padha bakal luwih cedhak lan wong sing beda bakal luwih adoh.. Jarak antarane rong vektor diitung nggunakake Jarak Euclidean.
3
Klasifikasi pasuryan
Sawise entuk vektor face-embedding, kita dilatih algoritma klasifikasi, K-tetangga paling cedhak (KNN), kanggo nggolongake wong saka vektor semat.
Upaminipun ing organisasi ana 1000 karyawan. Kita nggawe embeddings pasuryan kabeh karyawan lan nggunakake vektor embedding kanggo nglatih algoritma klasifikasi sing nampa vektor face-embedding minangka input lan ngasilake jeneng wong..
Pangguna bisa ngetrapake saringan sing ngowahi piksel tartamtu ing gambar sadurunge dilebokake ing web. These changes are imperceptible to the human eye but are very confusing for facial recognition algorithms – ThalesGroup
https://www.engati.com/blog/facial-recognition-systems Miturut Aniket Maurya
Artikel 6:What are the applications of the Facial Recognition System?

Airports
People entering and exiting airports can be tracked using facial recognition systems. The technology has been used by the Department of Homeland Security to identify people who have overstayed their visas or are under criminal investigation.
Mobile phone companies
Face recognition was first used by Apple to unlock its iPhone X, and the technology was carried over to the iPhone XS. Face ID verifies that you are who you say you are when you access your phone. According to Apple, the odds of a random face unlocking your phone are one in a million.
Colleges & universities
Nyatane, facial recognition software can play a role. Your professor might find out if you skip class. Don’t even consider having your bright roommate take your exam.
Social media
When you upload a photo to Facebook, it uses an algorithm to detect faces. If you want to tag people in your photos, the social media company will ask you. It can link to their profiles and recognize faces with an accuracy of 98%.
Marketing and advertisement campaigns
When marketing a product or an idea, marketers frequently consider factors such as gender, age, and ethnicity. Even at a concert, facial recognition can be used to identify specific audiences.
New tech brings new opportunities
Advancements in facial recognition systems and computer vision have taken great leaps. Nanging iki mung wiwitan revolusi teknologi. Bayangake carane kuat duo algoritma pangenalan pasuryan lan teknologi chatbot!
Ora kasep kanggo dadi bagian saka gerakan iki.
Miturut Aniket Maury
Artikel 7:Kontrol Akses tanpa tutul

Pangenalan rai minangka salah sawijining cara otentikasi tanpa tutul sing diadopsi kanggo kontrol akses lan sistem interkom lawang., minangka bagéan saka paramèter jalur tanpa kontak ing desain bangunan generasi paling anyar.
Pandemi Coronavirus wis nyebabake tuwuhing syarat lan aplikasi teknologi lan produk bebas tutul ing papan kerja lan lingkungan multi-tenant kanggo nyuda frekuensi kontak antarane individu., kanthi mangkono mbantu nyuda risiko panularan virus.
Mulane, cara otentikasi sing ngidini pangguna kanggo ngenali awake dhewe tanpa piranti nutul fisik (teknologi kayata RFID, NFC, Bluetooth – lan saiki pasuryan pangenalan, mesthi) dadi pilihan sing disenengi kanggo interkom lawang lan sistem kontrol akses.
Bisa pangenalan pasuryan bisa diapusi dening foto?
Sistem kontrol akses pangenalan pasuryan AI paling anyar – kayata piranti Tommi – uga nggabungake anti-spoofing 'liveness’ deteksi, nggunakake kamera tambahan sing dibangun kanggo ndeteksi kesadaran lan gerakan rai 3 dimensi.
Artikel 8:Apa keuntungan saka Access Control pangenalan rai?

Otentikasi pangguna tanpa tangan
Salah sawijining tren paling cepet ing desain lan teknologi bangunan yaiku aplikasi pengalaman pangguna tanpa tutul. Kombinasi ekspansi kanthi cepet ing urip multi-tenant & papan kerja lan pandhemen Coronavirus nyebabake kabutuhan kanggo urip lan lingkungan kerja tanpa kontak. Ngapikake keamanan
Ngapikake keamanan
Piranti Pangenalan Rai generasi paling anyar nyedhiyakake otentikasi sing akurat lan aman banget, yen dibandhingake karo cara akses tradisional kayata kode PIN utawa entri lawang keyfob.
Cepet, manajemen trep lan remot saka ID panganggo Tambah, njabut lan kontrol akun Panganggo iku gampang lan prasaja kanggo administrator sistem lan bisa kebak ngatur mbatalake.
Dene otentikasi liwat piranti fisik mbutuhake fob utawa kertu kanggo diserahake utawa dikirim (lan bali), ID pangguna anyar bisa digawe lan dipateni dening administrator sistem (kayata keamanan, HR utawa concierge personel) saka sembarang situs remot nggunakake platform manajemen basis maya, Ngartekno nyepetake proses kanggo ngirit wektu lan dhuwit.
Ora ana piranti bukti asli sing dibutuhake
Akeh cara mlebu lawang lan identifikasi akses mbutuhake nggunakake piranti fisik kanggo keasliane – kayata keyfob, kertu RFID utawa smartphone. Apa pangguna lali utawa ilang 'piranti’ (utawa luwih elek – wis dicolong), banjur padha ora bisa ngakses bangunan.
Piranti sing otentikasi’ pangenalan pasuryan bakal tansah, mesthi, karo kowe!
Integrasi karo platform liyane
Sistem kontrol akses pangenalan rai uga bisa digabungake karo platform logistik lan sistem liyane, kayata wektu & rawuh, sistem pembayaran otomatis utawa sistem manajemen bangunan, mbantu ngembangake lingkungan bangunan sing cerdas.
Artikel 9: Pangenalan rai vs. Biometric Vena Palm ---5 Bedane Penting
Pangenalan rai lan urat telapak tangan minangka rong biometrik utama ing pasar saiki, nanging padha polar ngelawan ing akeh cara.
Carane padha bisa?
Teknologi pangenalan rai dianggo kanthi pemetaan geometri unik saka pasuryan wong, kayata jarak saka dagu menyang bathuk, jarak antarane mripat, dawa jawline, lsp.
Teknologi urat sawit dianggo kanthi nggunakake sinar infra merah kanggo nggambar pola urat unik saka telapak tangan wong, ngukur liwat 5 yuta titik data ing struktur vena.
Kanthi loro biometrik, informasi iki banjur bakal diowahi dadi kode ndhelik sing dadi ID biometric unik wong. Nalika padha mindai pasuryan utawa telapak tangan, kode biometrik sing wis dicenthang marang kode ana ing sistem, lan yen cocog, padha dikenali.
Nanging nalika asil pungkasan - identifikasi - bisa uga padha, cara loro biometrik iki entuk iki dramatically beda. Iki duwe sawetara akibat penting.
Iki minangka limang prabédan utama antarane pangenalan rai lan urat palem sing kudu sampeyan ngerti sadurunge milih bisnis sampeyan..
1. Privasi
Bentenane paling gedhe ing antarane pangenalan rai lan biometrik urat palem yaiku ing babagan privasi.
Pangenalan rai wis nampa kritik sing nyebar ing sawetara taun kepungkur amarga masalah privasi sing ditimbulake..
Amarga pasuryan sampeyan katon ing ngendi wae, kamera pangenalan pasuryan bisa gampang ngenali sampeyan saka kadohan, supaya sampeyan bisa dilacak ing umum lan nggawe risiko privasi serius.
urat sawit, ing sisih liyane, iku privasi-by-design. Amarga pola urat telapak tangan sampeyan ndhelikake ing tangan sampeyan, mbutuhake kombinasi cahya infra merah lan kamera ultra-HD sing cedhak kanggo njupuk.
Dadi, beda karo pangenalan rai, mokal pola urat telapak tangan sampeyan bisa dijupuk saka kadohan. Kanggo dikenali, sampeyan kudu kanthi sengaja mindai telapak tangan liwat pemindai vena palem - ora bisa dijupuk tanpa idin sampeyan.
Iki sing ndadekake urat sawit minangka biometrik adhedhasar persetujuan, menehi kaluwihan cetha liwat pangenalan rai ing syarat-syarat privasi.
2. Accuracy
Kajaba saka privasi, Akurasi minangka prabédan paling gedhe nomer loro ing antarane pangenalan rai lan urat palem.
Akurasi biometrik diukur kanthi rong faktor: Tingkat Penolakan Palsu (FRR), lan Tingkat Penerimaan Palsu (Adoh). Sing ngisor nomer, biometrik luwih akurat.
FRR ngukur kemungkinan pangguna sing sah bakal ditolak akses sing salah, dene FAR ngukur kasempatan pangguna sing ora sah bakal diijini akses sing ora bener.
Pangenalan rai duwe FAR lan FRR paling dhuwur ing kabeh biometrik ing pasar. Kosok baline, vena palm nduweni paling ngisor - nggawe 260 kaping luwih akurat ing syarat-syarat FRR, lan 130 ewu kaping luwih akurat ing syarat-syarat FAR.

Kajaba iku, pangenalan rai duwe cacat tambahan: iku ora merata akurat kanggo kabeh wong. Algoritma pangenalan pasuryan wis kabukten kurang akurat kanggo wanita lan wong sing duwe warna.
Sembarang teknologi identifikasi kudu padha akurat kanggo kabeh wong, amarga bebaya saka identifikasi ora akurat banget dhuwur. Inaccurate identification makes it possible for you to be misidentified as someone else, which has potentially dire consequences (particularly when used by law enforcement).
It’s also just plain inconvenient. Being misidentified and incorrectly denied access to something that’s yours is extremely annoying, and it defeats one of the core benefits of biometrics in the first place: convenience.
So in terms of accuracy, facial recognition performs worse than virtually any other biometric, making palm vein the clear winner.
3. Security
Facial recognition’s privacy risks and reduced accuracy also have a third consequence: reduced security.
The reduced accuracy of face recognition makes it more likely to misidentify users, potentially allowing access to unauthorized personnel and creating security risks.
But the biggest security risk of facial recognition is its vulnerability to spoofing. Since your face is exposed everywhere you go, it’s much easier for hackers to forge a 3D image of your face to fool a facial recognition device.
With palm vein, since your vein pattern is concealed inside your hand, it can only be captured when you deliberately scan your palm. Otherwise, it’s completely hidden, making it nearly impossible for a thief to forge or steal it.
These two features of palm vein — the increased accuracy and the fact that it’s internal — make it generally a much more secure biometric than facial recognition.
4. Convenience
There is one key advantage that facial recognition has over all other biometrics: convenience.
Despite the security and privacy risks associated with it, the fact that face recognition technology can automatically identify a user from a distance makes it very convenient if the user consents to this.
For example, face recognition on modern smartphones (such as Apple’s Face ID feature) allows users to unlock their phone just by looking at it. How convenient!
Kajaba iku, the privacy risks of facial recognition don’t apply to smartphones because the user’s biometric data is stored directly on the device, rather than in a database, so it can’t be used for surveillance purposes.
This makes facial recognition a seamless, convenient choice for unlocking smartphones. However, when used on public surveillance systems instead of personal devices, the privacy risks of facial recognition greatly outweigh the convenience benefits.
urat sawit, ing sisih liyane, doesn’t have the long-range automatic identification capabilities that facial recognition has, since it requires a close-up (but contactless) scan of the palm to identify the user. So while this gives it important privacy and security benefits, it could potentially be seen as a drawback in terms of convenience.
Kajaba iku, because palm vein is newer and less familiar, it arguably has a bigger learning curve than older biometrics (such as fingerprint), or highly intuitive biometrics (such as facial recognition, where you don’t actually have to do anything to be identified).
However, the simple, ergonomic motion of palm vein means that it’s still an easy-to-use and user-friendly biometric. Nonetheless, facial recognition, especially on personal devices, does have significant convenience benefits that palm vein doesn’t.
This makes palm vein ideal when shared among large numbers of people (e.g., employees and customers), while facial recognition is ideal for individual use on personal devices (e.g., smartphones and tablets).
5. Legal Compliance
In recent years, major privacy regulations have been popping up around the globe. Since the creation of the GDPR in 2016, many major economies have created their own GDPR copycat laws, making privacy regulations a worldwide trend.
Because of this, companies today have more restrictions than ever on data collection.
And the number-one factor in privacy regulations around the world is consent. Companies must obtain explicit user consent before they’re allowed to capture user data, or they face significant legal risks.
Because of this, the importance of privacy-friendly technologies is more important than ever. Companies that implement such technologies have much less legal risk to worry about, and much less hassle to deal with.
Since facial recognition allows for the possibility of capturing a person’s data without their consent, it is critical for companies to put safeguards in place to ensure that they’ve obtained explicit, verifiable consent before collecting user data — or they risk facing serious fines.
The benefit palm vein has over facial recognition is that, since it has consent automatically built-in, it has far less legal risk associated with it.
With palm vein, there’s no question whether a user consented to give their biometric data or not, because it can’t be captured without a person’s explicit interaction with the terminal.
And because automatic, forced capturing of biometric data isn’t possible with palm vein (as it is with facial recognition), it is automatically in-line with the consent-focused guidelines in most data protection regulations.
This makes palm vein the more convenient, less risky, hassle-free choice for companies looking to implement biometrics in their business.
Conclusion
Facial recognition and palm vein are powerful biometric technologies with a large range of applications, but they are complete opposites in many ways.
For public and business use, palm vein has many advantages over facial recognition, offering various privacy, security, and accuracy benefits that facial recognition doesn’t have.
Kajaba iku, ing babagan kapercayan lan risiko legal, vena sawit umume minangka pilihan sing kurang beresiko kanggo perusahaan sing pengin ngetrapake biometrik ing bisnis amarga desain sing fokus ing privasi..
Kanggo digunakake ing piranti pribadi, nanging, pangenalan rai minangka cara otentikasi sing trep lan gampang digunakake sing ora duwe risiko privasi sing padha karo jinis pangenalan rai sing digunakake ing kamera pengawasan..
Faktor-faktor kasebut nggawe biometric urat palem sing cocog kanggo panggunaan bareng (e.g., digunakake dening pelanggan utawa karyawan), dene pangenalan rai minangka pilihan sing apik kanggo otentikasi piranti pribadi.
Saben biometrik duwe pro lan kontra sing unik. Kanggo sinau luwih lengkap babagan jinis biometrik liyane ing pasar lan mbantu nemtokake endi sing cocog kanggo bisnis sampeyan, check out our ebook exploring all of the different biometrics on the market.
Artikel 10:The sense behind the biometric measures

Thanks for your blog, nice to read. Do not stop.