This article explores the core value of DM codes in the laser marking industry: through CKVision SDK's machine vision recognition algorithms and image preprocessing technology, it effectively resolves reading challenges such as metal reflections; implements quality grading based on ISO standards to monitor and optimize laser processes in real-time; and combines "on-the-fly" capture with coordinate calibration technology to significantly enhance production line capacity and alignment accuracy while ensuring full lifecycle traceability.

CKVision SDK 6.0 is a professional machine vision development toolkit for the industrial vision inspection field. The SDK provides complete functional modules including 2D/3D image processing, object detection, precision measurement, defect detection, and intelligent recognition. It can be widely used in industrial automation scenarios such as intelligent manufacturing, quality inspection, and robotic vision guidance.

In the field of machine vision, matching technology is one of the core technologies for target positioning, recognition, and tracking. From early pattern matching to geometric matching, contour matching, and today’s AI deep learning era, matching algorithms have evolved over decades. This paper systematically reviews the development history of this technology, discusses algorithmic paths for performance optimization, and re‑examines the value of traditional matching methods amid the AI wave.

In recent years, Flexible Vibrating Disk has rapidly penetrated automated production lines in 3C electronics, automotive parts, medical devices and other fields thanks to its advantages of multi-material compatibility and fast changeover. However, without highly reliable machine vision support, the potential of flexible feeding systems will be greatly compromised. This paper deeply analyzes the working principle and core challenges of Flexible Vibrating Disk, systematically elaborates the key role of CKVision Image Processor in feature detection, pose recognition and real-time feedback control, and reveals the advantages of capacity improvement, changeover efficiency and quality assurance brought by their in-depth integration through typical cases. Finally, the future development trends are prospected.

Warm Spring with Bright Scenery, Forging Ahead Together. From Shanghai New International Expo Centre to Shenzhen World Exhibition & Convention Center, two grand industrial vision events held over nearly two weeks — Vision China 2026 Shanghai and ITES Shenzhen Industrial Exhibition 2026 — have come to a successful conclusion. As a company deeply engaged in […]

From March 25 to 27, 2026 China (Shanghai) Machine Vision Exhibition and Machine Vision Technology & Application Conference will grandly open at Halls W4 and W5 of Shanghai New International Expo Center!

As a benchmark exhibition in China’s industrial sector, the 2026 ITES Shenzhen Industrial Exhibition will grandly open from March 31 to April 3 at Shenzhen World Exhibition & Convention Center (Bao’an). Centered on precision component manufacturing

OCR and OCV Technologies: From Optical Recognition to Intelligent Visual Inspection Ⅰ. Origins and Early Development OCR (Optical Character Recognition) traces its history back to the early 20th century. In 1914, physicist Emanuel Goldberg invented a machine capable of reading characters and converting them into telegraph code, considered the prototype of OCR technology. In 1929, […]

On January 23, 2026, at this wonderful moment marking the end of the old year and the beginning of the new, all CKVision employees gathered together to celebrate the long-awaited 2025 Year-End Dinner Party. The venue was adorned with bright lanterns and colorful decorations, filled with joy and laughter, and permeated with a festive atmosphere everywhere.

In machine vision systems, image quality directly affects the accuracy and reliability of subsequent processing tasks. During image acquisition, transmission, and storage, images inevitably suffer from various types of noise contamination, including sensor thermal noise, quantization noise, and transmission interference. These noise sources severely degrade image quality and impact the performance of critical algorithms such as feature extraction, object recognition, and edge detection. Image filtering, as a core technology in machine vision preprocessing, aims to suppress noise while preserving useful information in images, such as edges, textures, corner points, and other important features.