Stereo vision, resulting in the knowledge of deep information in a scene, is of great
importance in the field of machine vision, robotics and image analysis. In this article, an …

This paper presents a survey on existing stereo vision algorithms. Generally, stereo vision
algorithms play an important role in depth estimation. The quality of disparity map as well as …

In this paper, we present a novel technique for optical 3-D surface reconstruction by using
line-scan cameras and structured light in combination. The approach generating structured …

In the lens-based imaging model, the Scheimpflug principle is expressed as the object
plane, the image plane, and the lens plane intersect in a line. With this principle, the focused …

The application of imaging techniques in plant and agricultural sciences had previously
been confined to images obtained through remote sensing techniques. Technological …

Stereoscopic 3D reconstruction is an important algorithm in the field of Computer Vision,
with a variety of applications in embedded and real-time systems. Existing software-based …

Computational performance of embedded systems heavily increased during last decade
and tasks, which used to have a real time solution only in PC based vision systems are …

Stereo Vision, a technique aimed at inferring depth information from stereo images, has
been used in a wide range of computer vision applications, with real-time requirements in …

Disparity estimation in stereoscopic vision is a vital step for the extraction of depth
information from stereo images. This paper presents the hardware implementation of a …

In deep learning-based local stereo matching methods, larger image patches usually bring
better stereo matching accuracy. However, it is unrealistic to increase the size of the image …