Vehicle Tracing with Number Plate OCR from CCTV Footage
Powered by Krishna Intelligence — AI-powered forensic CCTV analysis for investigators
The full picture
Vehicle incidents generate India's most common CCTV requests: a hit-and-run outside a Rajkot showroom, a two-wheeler lifted from outside a Jamnagar clinic, a car scraped in a society lane, a tanker that dumped debris and drove off. In each case the question is identical — which vehicle, coming from where, going where — and the raw material is scattered: the society's gate camera, two shop cameras down the road, a municipal camera at the junction. Manually tracing one vehicle through this patchwork means reading blurry plates frame by frozen frame across hours of multi-source footage, and the practical result is that unless someone was gravely hurt, the trace never happens and the complainant absorbs the loss.
Krishna Intelligence automates the trace. All collected footage — any mix of DVR exports — goes through a batch scan whose vehicle detection isolates every car, two-wheeler, truck and auto appearance, while number-plate OCR reads visible plates into searchable text. A full or partial registration then queries the entire footage set at once: every camera where GJ-10 and those digits appear, timestamped and ordered, assembling the vehicle's route through the area in minutes. Where plates are unreadable — night glare, angle, mud — the colour and vehicle-type filters carry the trace: every white hatchback between 9:40 and 10:00 PM across all cameras is a reviewable shortlist, not a needle hunt, and one clean frame from any camera in the chain recovers the registration.
The output supports what comes next. For a police complaint, the SHA-256 verified report packages the vehicle's appearances — frames, plate reads, camera-by-camera timeline — in tamper-evident form an investigating officer can act on immediately, shared by WhatsApp link. For insurance, the documented sequence of the collision and the offending vehicle's identification substantiates the claim. For societies and businesses, the same capability answers routine questions — when a delivery vehicle actually arrived, whether a claimed visit happened — from footage already being recorded. India's roads are watched by millions of private cameras; number-plate OCR is the difference between that coverage being an anecdote — "it must be on someone's CCTV" — and being a search-able record that regularly finds the vehicle.
What you get
Plate Search Across All Footage
OCR reads visible plates into text, so a full or partial registration queries every camera's footage at once instead of frame-by-frame squinting through hours of paused video.
Route Reconstruction
A traced vehicle's appearances across gate, shop and junction cameras assemble into a timestamped route through the area in minutes, ready to hand any investigating officer.
Partial-Plate Workflows
Witness fragments — "GJ-10, ending in 7" — become filtered searches, matching Indian reality where nobody notes a full registration of an offending vehicle down completely.
Trace Without a Readable Plate
Colour and vehicle-type filters shortlist every white hatchback in the window; one clean frame anywhere in the chain recovers the number for the whole chain of cameras.
Mixed-Source Tolerance
Society DVR exports, shop cameras and dashcam clips analyse together on one timeline, whatever their brand or quality, letting every available camera in the area contribute to the trace.
Complaint-Ready Output
SHA-256 verified reports with frames, plate reads and route timeline give police and insurers something actionable on day one of the complaint instead of weeks later.
How to start
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Step 1
Collect footage from every camera along the vehicle's plausible route — society, shops, junctions.
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Step 2
Batch-scan in Krishna Intelligence to detect all vehicles and OCR all visible plates.
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Step 3
Search by full or partial registration, or filter by vehicle type and colour in the time window.
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Step 4
Export the SHA-256 verified route report and share it with police or the insurer via WhatsApp link.
Common questions
The plate is blurry in our camera. Is the trace dead?
No — this is why multi-camera tracing works. Use colour and vehicle-type filters to follow the vehicle as an object across cameras: every silver sedan in the fifteen-minute window is a short reviewable list. The vehicle only needs to pass one camera at a readable angle — often a shop camera at gate height — for OCR to recover the registration and confirm the chain.
A witness only remembers part of the number. Can we search on that?
Yes — partial matching is the designed workflow, because real witnesses recall fragments: the state code, two digits, a series letter. The OCR index of all plate reads across the footage is queried on the fragment, returning candidate vehicles with their frames and timestamps. Combining the fragment with the witness's colour and vehicle-type description usually narrows results to one or two candidates.
Will police act on a report like this?
A complaint accompanied by organised evidence — the offending vehicle's frames, plate reads, and a camera-by-camera timeline, each element SHA-256 hashed against tampering — gives the investigating officer immediate working material instead of a footage-collection task. Complainants who arrive with verified findings consistently see faster registration and follow-up than those reporting "it must be on CCTV somewhere," because the first investigative step is already done.
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Vehicle Tracing with Number Plate OCR from CCTV Footage — open Krishna Intelligence now, or message us and we will set it up with you on WhatsApp, in Gujarati or English.