BACKGROUND AND OBJECTIVE The effective processing of biomedical images usually requires the interoperability of diverse software tools that have different aims but are complementary. The goal of this work is to develop a bridge to connect two of those tools: ImageJ, a program for image analysis in life sciences, and OpenCV, a computer vision and machine learning library. METHODS Based on a th...

In this paper, design and implementation of an interactive open architecture computer vision software package called Ch OpenCV is presented. Benefiting from both Ch and OpenCV, Ch OpenCV has many salient features. It is interactive, capable of interface with binary static or dynamical C/Cþþ libraries, integrated with advanced numerical features and embeddable. It is especially suitable for rapi...

In today’s advancing market, the growing performance and decreasing price of embedded processors are opening many doors for developers to design highly sophisticated solutions for different end applications. The complexities of these systems can create bottlenecks for developers in the form of longer development times, more complicated development environments and issues with application stabil...

In this paper, we implement a dehazing algorithm using dark pixel detection in MatLab and C++/OpenCV. The algorithm is originally proposed in Yu et al.’s paper. The simplicity and effectiveness of the algorithm make it possible for us to run the C++/OpenCV implementation on Android phones through android NDK with reasonable speed. Keywords—dehaze; image processing; mobile application; computer ...

The program that displays the user's desired print color is called recognition technology. It compares codes already provides with image whose colors we want to know. Let's begin by asking, We are aware of a disability very common in humans "color blindness." Though it humans, most people can live because, as long you don't think too much about colors, won't affect your overall performance. fut...

Python is a popular language widely adopted by the scientific community due to its clear syntax and an extensive number of specialized packages. For image processing or computer vision development, two libraries are prominently used: NumPy/SciPy and OpenCV with a Python wrapper. In this paper, we present a comparative evaluation of both libraries, assessing their performance and their usability...