ReCAP for emergency contact recognition in Australian broadcasts

An emergency contact graphic can appear for only a few seconds during a live bulletin: a fire service number in a Melbourne warning, a police contact after a Sydney incident, or a support line following a regional broadcast. A missed digit or outdated number can send viewers towards the wrong service. Automatic visual analysis can identify, extract and preserve that information while it moves through a live production chain.

These graphics are not simply subtitles or lower thirds. A contact card may contain a phone number, address, website, organisation name and emergency symbol, sometimes in several languages. It may replace an earlier card, sit over moving footage or arrive as a full-screen slate. Recognising the words is only one part of the task; the system must also distinguish actionable contact details from sports results, advertising claims and news headlines that resemble them.

ReCAP, the EU-funded Real-time Content Analysis and Processing initiative, develops tools for broadcast-quality video analysis, automatic metadata extraction, video-quality monitoring, face and logo recognition, and duplicated-content detection. Its technical focus is directly relevant to this use case because emergency information is often embedded in broadcast graphics rather than supplied through a separate data feed. The opportunity is to turn fleeting visual information into structured, traceable metadata without treating recognition as a substitute for verification by the issuing authority.

For Australian broadcasters, ReCAP for automated recognition of emergency contact graphics in public broadcasts is best treated as a repeatable workflow across production, live broadcasting and media asset management. The objective is to help producers find useful information, give editors a searchable record and preserve human approval when public safety, privacy or jurisdiction make an automatic result consequential.

Why emergency graphics need machine assistance

Live operations make manual capture unreliable. A producer may be managing a breaking story, sponsor announcements and social copies simultaneously while an emergency card appears over the clean feed for a single break. Manual logging can lose the exact time, wording and visual context of that graphic. Automatic detection creates a timestamped record, making the information searchable for rundown, compliance and archive teams.

Recognition must also be conservative. A false positive can classify an advertising hotline as an emergency contact and send it into the wrong workflow. A false negative can hide a genuine instruction. Useful performance therefore combines correct text extraction with correct classification, confidence scoring and a clear route for uncertain results. Speed matters, but a slightly delayed match with verification is safer than an instant but misleading alert.

For Australian audiences, this matters because emergency information often combines a national number with state, council or specialist-service contacts. A graphic may display 000, the 112 emergency number available from mobile phones, or a non-emergency line whose purpose must remain clear. During a crisis, confusing an emergency service with a support service can waste valuable time. The system should preserve labels and symbols rather than reducing a card to digits alone.

What the ReCAP research provides

ReCAP addresses several parts of a modern broadcast pipeline at once. In addition to visual recognition, the initiative targets real-time processing, quality monitoring and automatic metadata generation. The consortium’s goals, milestones and demonstrations are presented on the ReCAP project website, where the broader technical scope can be examined before an emergency-specific application is planned.

Applied to contact graphics, those capabilities suggest a staged workflow. Frame analysis can locate likely text and graphic regions. Optical character recognition can then propose the visible wording, while logo recognition can help associate a card with an agency. Metadata extraction can organise that information into fields such as service type, telephone number, address, jurisdiction and appearance time, with confidence and source frames retained at each stage.

This is an application built from ReCAP’s research capabilities, not a claim that every emergency-contact function is already a finished product. Emergency overlays introduce domain-specific challenges, including rapidly changing numbers, stylised lettering, transparent backgrounds and deliberate visual similarity between notices. A dependable implementation would combine general-purpose analysis with a separately validated emergency-information model and broadcaster editorial rules.

Turning visual overlays into structured metadata

A practical detector can begin with layout and change detection. Contact cards often have stable boundaries, repeated placement, high-contrast lettering or a sudden appearance that differs from the underlying programme. Candidate regions can be tracked across consecutive frames, reducing isolated OCR errors. Full-screen slates need a different layout profile from lower-thirds, but both can contribute to one contact-information record when the same number and agency recur.

Australian number formats offer useful validation cues, although they are not absolute proof. National emergency numbers include 000 and 112, service numbers often begin with 1300 or 1800, and mobiles begin with 04. Landline area codes vary by place, including 02 for Sydney, 03 for Melbourne, 07 for Brisbane and 08 for Perth. International cards may use +61 and omit the domestic trunk prefix. The recogniser must preserve the original string separately from any normalised interpretation.

Classification should use more than a number prefix. An organisation name, a recognisable NSW RFS, CFA or state emergency-service logo, and the words Emergency Warning can support the category decision. Multilingual cards may carry Arabic, Mandarin, Vietnamese or community languages, including Aboriginal and Torres Strait Islander languages. Colour and layout alone remain weak evidence because broadcast designers change graphics packages, and a red banner can belong to a breaking-news strap rather than a public-safety instruction.

Designing for Australian broadcast conditions

Australian production conditions range from the large studios of Sydney and Melbourne to regional stations in Newcastle, Hobart, Darwin and smaller centres. The ABC and SBS have distinct public-service remits, while Seven, Nine and Network 10 carry public-safety material through commercial networks and regional operators. A detection workflow must cope with different graphics packages, playout systems and transmission standards rather than assuming one broadcaster’s template.

Language and place names add another layer. Australia’s official Emergency Warning messages may be accompanied by state-agency branding, multilingual overlays or local place names that a general English OCR model may not handle reliably. The Newcastle case study provides additional context in the project’s public-facing communication, while practical Australian deployments would still require locally representative labelled examples and authority-specific terminology.

Regional and remote coverage creates genuine technical constraints. Satellite links and contribution feeds from parts of Western Australia or the Northern Territory may deliver lower bit rates, visible compression artefacts or intermittent frames. Municipal services may also supply contact details separately from the broadcast. The recogniser should report low-confidence results when the signal is poor, while producers confirm the authoritative number through the relevant state or local emergency service.

Measuring recognition, quality and duplication

Accuracy needs several measurements. Text detection and recognition should be evaluated against human-verified transcripts, but classification errors must be distinguished from character errors. Precision, recall and the time from first appearance to usable metadata are all relevant. A phone number presented as several contiguous segments can still be useful if the system preserves its reading order and flags uncertainty instead of joining unrelated values.

Video-quality monitoring complements OCR evaluation. Blur, blockiness, scaling artefacts and dropped frames can change the appearance of white text over moving backgrounds. Broadcast-quality assessment should consider the delivered stream, including compression and downscale-and-upscale effects, because a model tested on clean frames may fail during a live incident. Quality scores can also explain why a confidently formatted number was not visually legible.

Duplicate detection can support cross-channel monitoring without assuming that identical text always has identical meaning. The same 1300 information line may legitimately appear on ABC, SBS and commercial bulletins, while two state services can share part of a number. Matching should preserve source, time and graphic identity so editors can compare versions and locate an earlier correction. Deduplication then becomes a way to trace how public information changed, rather than merely a storage shortcut.

From detection to editorial operations

In a live gallery, detected contact information could appear as an internal prompt beside the programme feed, with a thumbnail, transcript, source timecode and confidence level. An editor can confirm or reject it before the approved record is attached to the asset and relevant distribution copies. This assists fast retrieval under pressure while keeping a person responsible for what is labelled as an emergency contact.

For catch-up services and media archives, structured metadata supports search by number, agency, location and service category. It can surface an emergency card in a long news archive, link separate appearances of the same notice and create a review trail for corrections. Accessibility teams could use verified text for captions or audio description, provided the workflow does not publish extracted digits before editorial checking.

Distribution beyond television makes version control especially important. Australian broadcasters commonly repurpose bulletins into vertical social clips, websites and streaming bulletins, and viewers may also receive follow-up messages through channels such as Telegram messaging. A contact shown on television should be checked against the issuing authority before it is copied into another format or channel, since cropping and re-rendering can obscure or remove essential context.

The same metadata can support post-broadcast audits and editorial training. Teams can examine whether the number, issuing body and correction remained consistent across programmes, and identify clips that lack an accessible text alternative. This evidence is valuable when a retrospective review must reconstruct what viewers saw and when. It also gives standards teams concrete material for improving graphics templates without blaming individual operators.

A practical path to implementation

Implementation should begin with a representative dataset, not a demonstration limited to polished studio cards. Australian examples need agency logos, state abbreviations, multilingual text, transparent overlays and degraded regional feeds, alongside negatives such as news hotlines, charity advertisements and sports contacts. Broadcast partners can label the visible text, category, issuing authority, jurisdiction and time range, preserving enough context to distinguish a genuine public-safety notice from ordinary contact information.

The metadata schema should specify how raw text becomes a structured contact record. It should retain the exact characters, detected language, confidence at text and graphic level, source channel, frame timestamp and whether a human approved it. Emergency identifiers such as 000 require stricter handling than general business numbers. Where a card contains several contacts, the system should preserve each association rather than flattening the graphic into one ambiguous string.

Deployment can proceed in stages: offline testing on recorded programmes, shadow mode beside live galleries without publishing results, and finally editor-assisted use with a clear fallback to manual capture. Thresholds should reflect the consequences of a miss and be reviewed with emergency communication specialists and Australian legal and editorial teams. Low-quality feeds should generate a quality warning, not a fabricated transcription.

A practical pilot needs named success measures, including character accuracy, category precision, detection latency and the proportion of cards correctly linked to an approved authority. It should also record how often editors reject or amend automatic results, since that exposes gaps in local vocabulary and graphic styles. The concrete next step is a labelled Australian test set of emergency-contact overlays, benchmarked against human-verified transcripts.