Camera calibration is a foundational process in computer vision, robotics, and 3D reconstruction. It determines the camera's intrinsic properties—including focal length, principal point, and lens distortion parameters—enabling precise correction of image geometry and conversion between pixel cooordi...
Image recognition inovlves identifying objects, scenes, or patterns within digital images through computational analysis. The typical pipeline includes preprocessing, feature extraction, model training, and classification. Preprocessing prepares raw images for analysis—common steps include resizing,...
This project demonstrates a pet cat detection system built around the Seeed Studio XIAO ESP32 S3 Sense board. The solution leverages computer vision techniques and embedded systems to monitor and analyze feline behavior in real time. The hardware setup includes the XIAO ESP32 S3 Sense development bo...
The task of distinguishing cats from dogs originates from a beginner-level Kaggle competition titled Dogs vs Cats. To gain deeper insights into Convolutional Neural Networks (CNNs), several classic models like LeNet, AlexNet, and ResNet were implemented using PyTorch. This exploration investigates h...
Invoice document processing relies heavily on accurate field extraction to streamline financial audits and tax compliance. Among various optical character recognition strategies, template matching remains a foundational technique for locating and decoding structured text within standardized forms. C...
A typical content-based image retrieval pipeline transforms visual data into discirminative feature vectors through three primary stages: descriptor computation, database indexing, and similarity ranking. This implementation employs a multi-modal feature fusion strategy combining chromatic statistic...
Reading Images In OpenCV, the cv::imread() function is used to load images from a file. This function returns a cv::Mat object, which is the primary data structure in OpenCV for storing image data. // Load a color image cv::Mat imgData = cv::imread("sample_image.png", cv::IMREAD_COLOR); Th...
Template matching is a computer vision technique used to locate predefined patterns with in images. In invoice recognition, this method identifies key fields such as invoice numbers, dates, and amounts by comparing them with stored templates. The process involves preprocessing, sliding window compar...
The task of this competition is to determine whether a facial image within a video is a Deepfake and output a probability score. Participants must develop and optimize detection models to handle diverse Deepfake generation techniques and complex scenarios, thereby improving the accuracy and robustne...
Creating Artistic Images with Neural Networks: Style Transfer and GAN Implementation Introduction Neural networks, particularly Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs), have demonstrated remarkable capabilities in generating and transforming visual art. This g...