feature extraction
Feature Extraction Techniques : – 1. SIFT – Scale-Invariant Feature Transform Idea: Find strong, unique points in an image that stay the same even if the image gets bigger, smaller, or rotated. Example: You zoom into a building photo — windows & corners remain detectable. Original Image: 🏛 Zoomed Image: 🏛 Rotation: 🏛⤾ (Same strong […]
Motion analysis
Motion analysis is the process of detecting and tracking the movement of objects in a sequence of images or videos. It is a key part of computer vision for applications like autonomous driving, video surveillance, robotics, and action recognition. 1. Optical Flow – “Where Things Are Moving” Put tiny arrows on everything that moves. Each […]
Texture Analysis
Texture Analysis: Step-by-Step Guide with Examples 1. Introduction to Texture in Images Texture refers to the spatial arrangement of intensity or color patterns in an image. It is widely used for classification, segmentation, and pattern recognition. Common approaches for texture analysis: Statistical methods (GLCM, LBP) Filter-based methods (Gabor filters, Laws’ texture energy) Texture-based segmentation 2. […]
image segmentation
Image Segmentation: Complete Guide with Examples 1. What is Image Segmentation? Segmentation is the process of dividing an image into meaningful regions or objects. It is commonly used for object recognition, tracking, and analysis. Segmentation approaches: Edge-based segmentation: Detect boundaries between regions. Thresholding: Separate regions based on intensity values. Region-based segmentation: Group pixels with similar […]
Haar Transform
1. What is the Haar Transform? The Haar Transform is a type of wavelet transform. It’s used to: Represent data in terms of averages (low-frequency components) and differences (high-frequency components). Analyze signals, images, or data for compression and feature extraction. In simple terms, the Haar Transform splits a dataset into “smooth” parts and “detail” […]
Slant Transform
Slant Transform widely used in image compression it is orthoganal and its computing is done at very fast rate. its kernal can be generated recursively like hadmards Transdorm. slant transform of order 2*2 is written as 2×2 Slant Transform — Step-by-step (HTML) Slant matrix S2 (definition) Basis vectors: DC = [1, 1], slope = […]
Walsh-Hadamard Transform
1. What is the Walsh-Hadamard Transform? The Walsh-Hadamard Transform (WHT) is a linear, orthogonal transform similar to the Fourier Transform but: Uses only +1 and -1 coefficients instead of sines and cosines. Very fast to compute, especially for powers-of-two-sized data (2×2, 4×4, 8×8…). Converts a signal or image from the spatial domain into the frequency […]
image Transformation
image transform is basically a representation of a two-dimensional signal image we know that image generally we have represented f of X y where x and y are the two spatial dimensions hence we say that it is a two dimensional signal that can be represented into a plane so the image signal holds this […]