This repository showcases the implementation of various image processing techniques on custom images. These techniques have been applied to enhance image quality, extract features, and improve the overall visual appeal of images.
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Image Negative Inverts pixel intensities to enhance visibility and reveal hidden details.
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Image Smoothing using Histogram Equalization Improves contrast and visibility by redistributing pixel intensities across the entire histogram.
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Edge Detection Identifies boundaries within an image, aiding in feature extraction and object identification.
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Canny Filter A precise edge detection algorithm that reduces noise and provides a cleaner edge map.
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Sepia Filter Adds a warm, brownish tone to images, creating a nostalgic or artistic effect.
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Otsu Threshold Segmentation Automatically determines an optimal threshold for image segmentation, separating regions with different characteristics.
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K-Means Segmentation Groups pixels into clusters based on similarity, allowing the separation of different objects or regions in an image.
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Contour Detection Identifies the boundaries of objects in an image, useful for object recognition and tracking.