machine vision

简明释义

机械视觉

英英释义

例句

1.The new packaging system utilizes machine vision to ensure proper labeling.

新的包装系统利用机器视觉来确保正确贴标。

2.Using machine vision, the robots can identify and sort products based on size and color.

通过使用机器视觉，机器人可以根据大小和颜色识别和分类产品。

3.The automotive industry relies on machine vision for inspecting parts during assembly.

汽车工业依赖于机器视觉在组装过程中检查零部件。

4.In agriculture, machine vision helps in detecting crop diseases early.

在农业中，机器视觉有助于早期检测作物疾病。

5.The factory implemented machine vision to enhance quality control in the production line.

工厂实施了机器视觉以增强生产线的质量控制。

作文

In today's rapidly evolving technological landscape, the term machine vision refers to the ability of a computer to interpret and understand visual information from the world. This technology integrates various fields such as computer science, artificial intelligence, and optics to enable machines to 'see' and process images in a way that mimics human vision. The applications of machine vision are vast and varied, ranging from industrial automation to medical diagnostics. One of the most significant advancements in machine vision has been its implementation in manufacturing processes. For instance, in assembly lines, machine vision systems can inspect products for defects at an incredible speed and accuracy. They use high-resolution cameras and sophisticated algorithms to analyze images, ensuring that only products meeting quality standards proceed to the next stage of production. This not only enhances efficiency but also reduces waste and operational costs, making it a crucial component in modern manufacturing.Moreover, machine vision is revolutionizing the field of autonomous vehicles. These vehicles rely on machine vision to navigate and interpret their surroundings. By processing images from multiple cameras, an autonomous vehicle can detect obstacles, read traffic signs, and even recognize pedestrians. This capability is essential for the safety and reliability of self-driving cars, as it allows them to make real-time decisions based on visual input.In the medical field, machine vision plays a pivotal role in diagnostics and surgery. For example, advanced imaging systems utilize machine vision to analyze medical images such as X-rays, MRIs, and CT scans. These systems can identify abnormalities with high precision, assisting doctors in making accurate diagnoses. Additionally, during surgical procedures, machine vision can guide robotic surgical instruments, enhancing the surgeon's capabilities and improving patient outcomes.The integration of machine vision into everyday life is also becoming more prevalent. In retail, for instance, machine vision systems are used for inventory management and customer analytics. By analyzing customer behavior through video feeds, retailers can optimize store layouts and improve the shopping experience. Similarly, in agriculture, machine vision helps monitor crop health and automate harvesting processes, leading to increased yield and efficiency.Despite its numerous benefits, the adoption of machine vision technology raises ethical considerations. Privacy concerns arise when machine vision systems are used in public spaces, as they can track individuals without their consent. Furthermore, the reliance on machine vision in critical applications necessitates rigorous testing and validation to prevent potential failures that could have dire consequences.In conclusion, machine vision represents a significant leap forward in how machines perceive the world around them. Its applications span various industries, from manufacturing to healthcare, showcasing its versatility and potential to enhance efficiency and safety. As technology continues to advance, it is crucial to address the ethical implications surrounding machine vision to ensure its responsible and beneficial use in society.

在当今快速发展的技术环境中，术语机器视觉指的是计算机从世界中解释和理解视觉信息的能力。这项技术结合了计算机科学、人工智能和光学等多个领域，使机器能够以类似人类视觉的方式“看见”和处理图像。机器视觉的应用广泛多样，从工业自动化到医疗诊断。机器视觉最重要的进展之一是其在制造过程中的实施。例如，在装配线上，机器视觉系统可以以惊人的速度和准确性检查产品缺陷。它们使用高分辨率相机和复杂的算法来分析图像，确保只有符合质量标准的产品才能进入生产的下一个阶段。这不仅提高了效率，还减少了浪费和运营成本，使其成为现代制造业的重要组成部分。此外，机器视觉正在彻底改变自动驾驶汽车领域。这些车辆依赖于机器视觉来导航和解释周围环境。通过处理来自多个相机的图像，自动驾驶汽车可以检测障碍物、读取交通标志，甚至识别行人。这种能力对于自驾车的安全性和可靠性至关重要，因为它使车辆能够根据视觉输入做出实时决策。在医疗领域，机器视觉在诊断和手术中扮演着关键角色。例如，先进的成像系统利用机器视觉分析医学图像，如X射线、MRI和CT扫描。这些系统可以高精度地识别异常，帮助医生做出准确的诊断。此外，在手术过程中，机器视觉可以指导机器人手术仪器，增强外科医生的能力，提高患者的治疗效果。机器视觉的整合也越来越普遍地进入日常生活。例如，在零售中，机器视觉系统用于库存管理和客户分析。通过分析视频中的客户行为，零售商可以优化商店布局，改善购物体验。同样，在农业中，机器视觉帮助监测作物健康并自动化收割过程，从而提高产量和效率。尽管有许多好处，但对机器视觉技术的采用也引发了伦理考虑。当机器视觉系统在公共场所使用时，会出现隐私问题，因为它们可以在未征得同意的情况下跟踪个人。此外，在关键应用中对机器视觉的依赖需要进行严格的测试和验证，以防止潜在的故障，这可能会导致严重后果。总之，机器视觉代表了机器感知周围世界的重大飞跃。它的应用跨越多个行业，从制造到医疗，展示了其多功能性和提高效率与安全性的潜力。随着技术的不断进步，必须解决围绕机器视觉的伦理问题，以确保其在社会中的负责任和有益的使用。