Digital ink recognition

With ML Kit's digital ink recognition API, you can recognize handwritten text and classify gestures on a digital surface in hundreds of languages, as well as classify sketches. The digital ink recognition API uses the same technology that powers handwriting recognition in Gboard, Google Translate, and the Quick, Draw! game.

Digital ink recognition allows you to:

  • Write on the screen instead of typing on a virtual keyboard. This lets users draw characters that are not available on their keyboard, such as ệ, अ or 森 for latin alphabet keyboards.
  • Perform basic text operations (navigation, editing, selection, and so on) using gestures.
  • Recognize hand‑drawn shapes and emojis.

Digital ink recognition works with the strokes the user draws on the screen. If you need to read text from images taken with the camera, use the Text Recognition API.

Digital ink recognition works fully offline and is supported on Android and iOS.

iOS Android

Key Capabilities

  • Converts handwritten text to sequences of unicode characters
  • Runs on the device in near real time
  • The user's handwriting stays on the device, recognition is performed without any network connection
  • Supports 300+ languages and 25+ writing systems, see the complete list of supported languages
  • Recognizes emojis and basic shapes
  • Keeps on-device storage low by dynamically downloading language packs as needed

The recognizer takes an Ink object as input. Ink is a vector representation of what the user has written on the screen: a sequence of strokes, each being a list of coordinates with time information called touch points. A stroke starts when the user puts their stylus or finger down and ends when they lift it up. The Ink is passed to a recognizer, which returns one or more possible recognition results, with levels of confidence.

Examples

English handwriting

The image on the left below shows what the user drew on the screen. The image on the right is the corresponding Ink object. It contains the strokes with red dots representing the touch points within each stroke.

    

There are four strokes. The first two strokes in the Ink object look like this:

Ink
Stroke 1 x 392, 391, 389, 287, ...
y 52, 60, 76, 97, ...
t 0, 37, 56, 75, ...
Stroke 2 x 497, 494, 493, 490, ...
y 167, 165, 165, 165, ...
t 694, 742, 751, 770, ...
...

When you send this Ink to a recognizer for the English language, it returns several possible transcriptions, containing five or six characters. They are ordered by decreasing confidence:

RecognitionResult
RecognitionCandidate #1 handw
RecognitionCandidate #2 handrw
RecognitionCandidate #3 hardw
RecognitionCandidate #4 handu
RecognitionCandidate #5 handwe

Gestures

Gesture classifiers classify an ink stroke into one of nine gesture classes listed below.

Gesture Example
arch:above
arch:below
caret:above
caret:below
circle
corner:downleft
scribble
strike
verticalbar
writing

Emoji sketches

The image on the left below shows what the user drew on the screen. The image on the right is the corresponding Ink object. It contains the strokes with red dots representing the touch points within each stroke.

    

The Ink object contains six strokes.

           

Ink
Stroke 1 x 269, 266, 262, 255, ...
y 40, 40, 40, 41, ...
t 0, 36, 56, 75, ...
Stroke 2 x 179, 182, 183, 185, ...
y 157, 158, 159, 160, ...
t 2475, 2522, 2531, 2541, ...
...

When you send this Ink to the emoji recognizer, you get several possible transcriptions, ordered by decreasing confidence:

RecognitionResult
RecognitionCandidate #1 😂 (U+1f62d)
RecognitionCandidate #2 😅 (U+1f605)
RecognitionCandidate #3 😹 (U+1f639)
RecognitionCandidate #4 😄 (U+1f604)
RecognitionCandidate #5 😆 (U+1f606)