Blob Center Localization Using Circular Prototype in Binary Images

This forked from an existing project. Ellipse features are commonly encountered in machine vision, and high-precision detection of ellipse centers is often required. If you are interested in how to precisely draw ellipses, refer to my earlier share: High-quality Ellipse Detection. Illustration: This is the source code for the paper. Important: Please use the citation of our IEEE TIP version instead of the arXiv version. The main contribution of the proposed ellipse detector is to both accurately and efficiently detect ellipses in images, which is universally considered as a tough and long-standing problem in the ellipse detection field.

本程序可以进行人脸检测，并且用矩形框出人脸位置。适合初学者使用，是个比较好的工具。

GCC-PHAT is a straightforward method for sound source localization. This MATLAB code allows angle localization of a sound source using a linear microphone array (with an example setup of 8 microphones). The code processes continuous sound signals (.wav format) captured by the array. Multiple sources can be detected as long as each source has distinct time intervals when emitting sound, without overlapping emission periods. This code is primarily designed for introductory learning purposes. It provides a basic understanding of GCC-PHAT and includes a brief documentation for guidance. Note: It is not suitable for those seeking to perform accurate or complex localization tasks. Key Features Processes linear microphone arrays (example: 8 microphones) Localizes sound angles based on non-simultaneous multiple sources Includes a basic documentation for learning purposes This tool is ideal for beginners aiming to understand the fundamental concepts behind GCC-PHAT in sound source localization.

这个M文件从二进制*.dat文件导入数据，用PSpice创建。它已针对Pspice 6.0 (DOS)、9.1 (Student)、10.0.3和16.2.0进行了测试。如果您使用的是其他版本的PSpice，您可能需要调整代码！M文件还通过PSpice的瞬态分析、交流和频率扫描进行了进一步测试。但是，它可能无法导入数字数据。如果你能提供一个用另一个版本的PSpice创建或包含不同数据类型的小示例文件，我很乐意提供帮助。

This project implements the technique of color transfer between images as described in the paper by Erik Reinhard, Michael Ashikhmin, Bruce Gooch, and Peter Shirley. One of the most common tasks in image processing is changing the colors of an image. This article presents a more general color correction method, which borrows color characteristics from one image to apply to another. The algorithm follows these steps: RGB to ℓαβ color space conversion: The transformation of the RGB color space into the ℓαβ color space, where the ℓ axis represents the lightness channel, and the α and β channels represent the color-opponent yellow-blue and red-green channels, respectively. Statistical and color correction: First, the mean value is subtracted from each channel's data points. Then, the data points are scaled by factors determined by the standard deviation of each respective channel. Final conversion to RGB: The result is converted back into the RGB color space. The MATLAB code for this procedure is contained in the color_transfer_built.m file. In lines 3 and 4 of the file, the source and target variables are modified to change the source and target images for color transfer.

Oracle provides several types for storing binary data such as BFILE, BLOB, BAW(L), and LONG RAW to handle data like images, sounds, and videos. Typically, in real-world projects, images and sounds are not stored directly in the database. Instead, the paths to the files are stored, and only when security requirements are high, the actual files might be stored in the database. BAW(L), LONG RAW, BLOB, and BFILE each serve different use cases depending on the data type and storage requirements.

提供 Informatica PowerCenter ETL 学习所需资料。

该算法是建立在离线传播模型下，不考虑多径效应、反射、折射等对信号强度有损耗的情况。算法中选用了NN、KNN、WKNN等几种常用的指纹定位算法。

本实验基于 MATLAB 的 GUI 展示 动态卷积 和 圆周卷积 的过程，帮助学生理解数字信号处理的基本概念。通过交互式界面，用户可以直观地观察卷积的变化及其在信号处理中的应用。