Corner detection (Harris) in Computer Vision - Model Pipeline Trace

Model Pipeline - Corner detection (Harris)

This pipeline detects corners in images using the Harris corner detection method. It finds points where the image brightness changes sharply in multiple directions, which often correspond to corners.

Data Flow - 5 Stages

1Input Image

1 image x 256 x 256 pixels x 1 channel (grayscale)→Load grayscale image→1 image x 256 x 256 pixels x 1 channel

A 256x256 pixel grayscale photo of a building corner

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2Gradient Computation

1 image x 256 x 256 x 1→Calculate image gradients in x and y directions using Sobel filters→1 image x 256 x 256 x 2 (gradient_x, gradient_y)

Gradient_x and Gradient_y matrices showing brightness changes

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3Structure Tensor Calculation

1 image x 256 x 256 x 2→Compute products of gradients and apply Gaussian smoothing→1 image x 256 x 256 x 3 (Ix2, Iy2, IxIy smoothed)

Smoothed matrices representing local gradient structure

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4Corner Response Calculation

1 image x 256 x 256 x 3→Calculate Harris response R = det(M) - k(trace(M))^2 for each pixel→1 image x 256 x 256 x 1 (corner response values)

Matrix with high values at corner points

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5Thresholding and Non-Maximum Suppression

1 image x 256 x 256 x 1→Keep points with response above threshold and suppress non-maxima→List of corner points (x, y coordinates)

Coordinates of detected corners like [(45, 60), (120, 130), (200, 210)]

Training Trace - Epoch by Epoch

No training loss curve because this is a non-learning algorithm

Epoch	Loss ↓	Accuracy ↑	Observation
1	N/A	N/A	Harris corner detection is a classical algorithm, no training involved

Prediction Trace - 5 Layers

Layer 1: Input Image

Layer 2: Gradient Computation

Layer 3: Structure Tensor Calculation

Layer 4: Corner Response Calculation

Layer 5: Thresholding and Non-Maximum Suppression

Model Quiz - 3 Questions

What does the gradient computation step produce?

A List of corner coordinates

B Smoothed image with less noise

C Matrices showing brightness changes horizontally and vertically

D Final corner response scores

Key Insight

Harris corner detection uses image gradients and local structure to find corners without any training. It relies on mathematical operations to highlight points where brightness changes sharply in multiple directions, which are useful for many computer vision tasks.