M 013 / 18301 Edge & Featuresalgorithm output

Shi–Tomasi Corners

edge & feature detection

Typeface · PT Mono

Real-world algorithm demonstration, applied to a NASA portrait.
Real-world algorithm demonstration, applied to a NASA portrait.Image: NASA / Eileen Collins · scikit-image (public domain)View source ↗

Prompt

Apply Shi–Tomasi Corners as a sparse technical overlay, placing small bright green dots at the strongest, well-defined corners and textured junctions. Space markers apart and avoid weak edges, flat surfaces, or dense redundant clusters. Keep the underlying photograph clearly visible. Keep the original subject and composition.

Identify

High-contrast corners are marked as keypoints1.

Principle

The smallest eigenvalue2 response of the local structure matrix selects good points.

Try it out

Compare the score and the distance.

Classification

Calculated image processing result.

Further examples · 7 images

Epipolar-geometry-church-corner-detection-right-image
02 Epipolar-geometry-church-corner-detection-right-imageA church exterior is shown with red crosses marking specific structural points. These markers identify high-contrast corners and textures where the smallest eigenvalue of the local structure matrix indicates a trackable feature point..gs8 (talk) · CC BY-SA 3.0 · Wikimedia Commons
Corner
03 CornerHandwritten characters are shown before and after corner detection. Red dots identify points of high curvature and junctions, demonstrating how the algorithm isolates unique local features for tracking or analysis.Retardo · Public domain · Wikimedia Commons
Fundamentalmatrix Linkes Bild
04 Fundamentalmatrix Linkes BildA monochrome street scene contains numerous red markers on building edges and vehicles. These points represent high-contrast corners selected to calculate the fundamental matrix between stereo images.Haldir · Public domain · Wikimedia Commons
Shi–Tomasi Corners, applied to “Brazil Belém Las Docas 02”
05 Shi–Tomasi Corners, applied to “Brazil Belém Las Docas 02”Cyan circles mark the intersection of beams and furniture edges in this outdoor cafe scene. These markers represent high-contrast corners identified through local structure matrix analysis.Cayambe (photo); processed for the Atlas · CC BY-SA 3.0 · Wikimedia Commons
Shi–Tomasi Corners, applied to “Stone bridge leading to a cemetery surrounded by trees in the compounds of Chion”
06 Shi–Tomasi Corners, applied to “Stone bridge leading to a cemetery surrounded by trees in the compounds of Chion”Points are detected along the railing edges of the stone bridge and the intricate roofline of the temple. The algorithm successfully isolates specific vertices in the complex foliage and architectural geometry.Basile Morin (photo); processed for the Atlas · CC BY-SA 4.0 · Wikimedia Commons
Shi–Tomasi Corners, applied to “Klagenfurt Viktring Quellenstrasse Strom-Verbundnetz 13022010 1580”
07 Shi–Tomasi Corners, applied to “Klagenfurt Viktring Quellenstrasse Strom-Verbundnetz 13022010 1580”Keypoints cluster on the sharp junctions of the transmission towers and the roof peak of the house. The effect ignores the low-contrast sky while highlighting structural intersections.Johann Jaritz (photo); processed for the Atlas · CC BY-SA 4.0 · Wikimedia Commons