affine image

简明释义

仿射图象;

英英释义

例句

1.An affine image 仿射图像 maintains parallel lines and midpoints, making it useful in architectural designs.

一个affine image 仿射图像保持平行线和中点，这使得它在建筑设计中非常有用。

2.The software uses algorithms to generate an affine image 仿射图像 from a set of control points.

该软件使用算法从一组控制点生成affine image 仿射图像。

3.In computer graphics, creating an affine image 仿射图像 allows for scaling and rotating objects without losing their proportions.

在计算机图形学中，创建一个affine image 仿射图像可以实现对象的缩放和旋转，而不会失去其比例。

4.The transformation of the original picture resulted in a distorted affine image 仿射图像 that still retained its basic structure.

原始图片的变换导致了一个扭曲的affine image 仿射图像，但仍保留了其基本结构。

5.By applying a matrix transformation, we can create an affine image 仿射图像 that reflects the original layout.

通过应用矩阵变换，我们可以创建一个反映原始布局的affine image 仿射图像。

作文

In the realm of computer graphics and image processing, the term affine image refers to a transformation that preserves points, straight lines, and planes. This means that an affine image is created by applying a series of linear transformations such as translation, scaling, rotation, and shearing to an original image. The significance of understanding affine image lies in its applications across various fields including computer vision, robotics, and even art. To illustrate this concept, consider a simple example involving a photograph. When we take a picture and later decide to resize it, rotate it, or even flip it, we are essentially creating an affine image. These transformations allow us to manipulate the image while maintaining the relationships between the objects within it. For instance, if we scale up an image, all the features within that image will grow proportionally, preserving their relative positioning. This property makes affine image transformations particularly useful in applications where maintaining the integrity of the scene is crucial.Moreover, the affine image concept extends beyond mere resizing and rotation. In advanced applications such as facial recognition systems, algorithms utilize affine image transformations to identify and match faces under different conditions, like varying angles or scales. By recognizing the affine image produced by these transformations, systems can achieve higher accuracy in identifying individuals, regardless of how they are presented in the image.Furthermore, in the field of robotics, affine image transformations play a vital role in navigation and object recognition. Robots often rely on cameras to perceive their surroundings. When a robot captures an image of an object, it may need to adjust for perspective changes as it moves. By applying affine image transformations, the robot can effectively interpret the object's position and orientation in relation to itself, thus enhancing its ability to interact with the environment.Art and design also benefit from the principles of affine image transformations. Graphic designers frequently use software that allows them to apply these transformations to create visually appealing layouts and compositions. By manipulating images through affine image techniques, artists can explore creative possibilities that would otherwise be limited by the constraints of the original image.In conclusion, the concept of affine image is fundamental in various domains, ranging from technology to art. Understanding its principles enables professionals and enthusiasts alike to harness the power of image manipulation effectively. As we continue to advance in technology, the relevance of affine image transformations will only grow, highlighting the importance of mastering this concept for anyone involved in image-related fields.

在计算机图形学和图像处理领域，术语仿射图像指的是一种保留点、直线和平面的变换。这意味着，通过对原始图像应用一系列线性变换，如平移、缩放、旋转和剪切，可以创建仿射图像。理解仿射图像的重要性在于其在计算机视觉、机器人技术甚至艺术等各个领域的应用。为了说明这个概念，可以考虑一个简单的例子，涉及一张照片。当我们拍摄一张照片并决定稍后调整其大小、旋转或翻转时，我们基本上是在创建仿射图像。这些变换使我们能够操纵图像，同时保持图像内对象之间的关系。例如，如果我们放大一张图像，图像内的所有特征都会按比例增长，从而保持它们的相对位置。这种特性使得仿射图像变换在需要保持场景完整性的应用中尤为有用。此外，仿射图像的概念不仅限于简单的调整大小和旋转。在面部识别系统等高级应用中，算法利用仿射图像变换来识别和匹配不同条件下的人脸，例如不同的角度或尺度。通过识别这些变换所产生的仿射图像，系统可以在识别个体时实现更高的准确性，无论他们在图像中是如何呈现的。此外，在机器人技术领域，仿射图像变换在导航和物体识别中也发挥着至关重要的作用。机器人通常依靠摄像头来感知周围环境。当机器人捕捉到一个物体的图像时，它可能需要根据移动情况进行透视变化的调整。通过应用仿射图像变换，机器人可以有效地解释物体在其自身位置和方向上的关系，从而增强其与环境互动的能力。艺术和设计同样受益于仿射图像变换的原理。平面设计师经常使用软件，允许他们应用这些变换来创建视觉上吸引人的布局和构图。通过通过仿射图像技术操纵图像，艺术家可以探索创作可能性，而这些可能性在原始图像的限制下是无法实现的。总之，仿射图像的概念在技术到艺术的各个领域都是基础。理解其原理使专业人士和爱好者能够有效地利用图像处理的力量。随着我们在技术上的不断进步，仿射图像变换的相关性只会增加，这突显了掌握这一概念对于任何涉及图像相关领域的人来说的重要性。