How India Uses Camera Trapping to Identify Individual Tigers by Their Unique Stripe Patterns
No Two Stripes Are the Same
A tiger's stripes are not just surface markings. They are set in the skin itself, the underlying pigmentation follows the same pattern as the fur above it, which means shaving a tiger would reveal the same design. Each animal's arrangement of stripes is unique: the spacing, the branching, the gaps, the slight asymmetry between left flank and right. Biologists treat this the way forensic labs treat fingerprints. The Wildlife Institute of India, which anchors much of the country's big cat research, uses this principle as the foundation of its individual identification work. A tiger photographed at Corbett and a tiger photographed at Bandhavgarh can be confirmed as different animals, or the same animal, purely from flank images.
The biological basis runs deeper than aesthetics. Stripe patterns in tigers are determined by a reaction-diffusion process during embryonic development, the same class of mechanism that produces spots on leopards and patterns on zebrafish. Because the process is sensitive to tiny variations in chemical gradients in the developing embryo, no two individuals land on the same outcome. This holds across subspecies: Bengal tigers and Amur tigers both carry individually unique patterns, though the overall density and width of stripes differs between them.
How Camera Traps Are Deployed Across Indian Reserves
A camera trap is a weatherproof unit fitted with a passive infrared sensor. When an animal breaks the sensor's beam, the camera fires. That is the whole mechanism. The sophistication is in the placement.
In a reserve like Nagarhole or Tadoba, field teams spend days reading the ground before a single camera goes up. Pugmarks in soft soil, scrape marks on trees, territorial spray on boulders, the compressed grass of a regular path, these signs tell researchers where a tiger moves habitually. Cameras go at flank height, angled to catch the side of the animal rather than a head-on shot, because the flank carries the identifying stripe field. Pairs of cameras are set on opposite sides of a trail so that both flanks are captured simultaneously.
The All India Tiger Estimation, conducted every four years by the National Tiger Conservation Authority, deploys tens of thousands of camera trap nights across tiger reserves. The 2022 estimation covered over 26 categories of landscape and logged images from more than 32,000 locations. That scale of deployment is what makes individual identification viable at the population level rather than just at individual study sites.
Reading the Image: From Photograph to Named Individual
Once images arrive from the field, the identification work begins. Early methods were manual: a researcher would print flank photographs and compare them against a reference library, stripe by stripe. The process was slow and prone to error when image quality was poor or the animal was partially obscured.
Software changed this. The most widely used tool in Indian tiger research is ExtractCompare, developed specifically for stripe-based identification. The program isolates the flank region of a tiger photograph, extracts the stripe pattern as a numerical vector, and compares it against every other pattern in the database. A match above a set confidence threshold flags a known individual. A pattern with no close match registers as a new animal and enters the database with its own record.
The Wildlife Institute of India has built a national database of individual tigers identified through this method. Each record carries the animal's sex, estimated age, reserve location, and a chronological log of every camera trap sighting. When a tiger appears in two different reserves, the database connects the sightings and documents the movement corridor between them.
What Individual Identification Has Changed
Before individual identification became standard, tiger population counts relied on pugmark census, the practice of casting or tracing paw prints and using their size and shape to distinguish animals. The method was widely criticised. Pugmarks change with substrate and gait. Different observers read the same print differently. The 2008 report by the Wildlife Institute of India found that pugmark-based counts had systematically overstated tiger numbers in several reserves for years.
Camera trapping with individual identification replaced that uncertainty with a count that can be defended photograph by photograph. The 2006 national estimate, conducted partly in the wake of the Sariska crisis when tigers disappeared from an entire reserve without the forest department noticing, found fewer than 1,500 tigers in India. The 2022 estimate, using camera traps and individual identification at scale, recorded 3,167 tigers. The increase reflects genuine population recovery driven by Project Tiger's protected area network, but it also reflects a counting method that no longer inflates numbers through misidentification.
Individual records also catch things aggregate counts miss. A tiger photographed repeatedly in one zone of a reserve and then absent for eighteen months is a signal. A female whose litter stops appearing in camera images is a signal. The data layer that individual identification adds turns a census into something closer to continuous monitoring.
The stripe pattern a tiger is born with stays with it for life. That permanence is what makes the whole system work, and what makes each camera trap image, however blurred or partially lit, a potential piece of evidence in a record that will outlast the animal itself.
India's tiger count has become one of the most closely watched wildlife statistics in the world. The number carries political weight, conservation funding decisions, and the credibility of an entire protected area system. The fact that it now rests on individual stripe identification rather than footprint inference means the count is, for the first time, something close to a true census rather than an estimate built on estimates.