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China Shenzhen City Haozhou Technology Co., Ltd.
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Shenzhen City Haozhou Technology Co., Ltd.
Shenzhen Haozhou Technology Co., Ltd. was established in 2014. It is a high-tech company specializing in R&D, design, production, sales, CMOS camera module, USB camera module, analog camera module, endoscope camera module, sensor chip and other high-quality camera modules technology enterprise. Provide a full range of processes, SMT, modules, assembly, packaging and other one-stop services. Passed IS09001 CE ROHS quality system certification. Products are widely used in nearly a hundred fields such as face recognition, biometrics, artificial intelligence, machine vision, drones, self-service terminals, smart homes, security monitoring, and medical applications.Warmly welcome OEM and ODM. We can design according to the drawings provided by customers. All of our products have a 2-year warranty, we are willing to provide customers with products that carry corporate culture and convey brand ideas to end users, we believe that success is built on a solid foundation and commitment to delivery. haozhou provides high quality camera modules with professional OEM design and manufacturing services to customers worldwide. We are carrying OmniVision, Sony, Samsung, Hynix, GalaxyCore... The main application areas: AI VR mobile phone, digital still camera, laptop, DV, PDA/handheld, toy, PC camera, security camera, automotive camera, tablet pc, visual doorbell, medical system, smart home, industrial image, recognition system, fingerprint identification system ...
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A brief discussion on edge detection in machine vision 2026-08-31 .gtr-container-xyz123 { font-family: Verdana, Helvetica, "Times New Roman", Arial, sans-serif; color: #333; line-height: 1.6; padding: 20px; box-sizing: border-box; font-size: 14px; } .gtr-container-xyz123 p { margin-bottom: 1em; text-align: left; font-size: 14px; } .gtr-container-xyz123 h3 { font-size: 18px; font-weight: bold; color: #0000FF; margin-top: 1.5em; margin-bottom: 0.8em; text-align: left; } .gtr-container-xyz123 ul { list-style: none !important; padding-left: 20px !important; margin-bottom: 1em; } .gtr-container-xyz123 ul li { position: relative !important; padding-left: 20px !important; margin-bottom: 0.5em !important; font-size: 14px; list-style: none !important; } .gtr-container-xyz123 ul li::before { content: "•" !important; color: #0000FF !important; position: absolute !important; left: 0 !important; font-size: 1.2em !important; line-height: 1 !important; } .gtr-container-xyz123 ol { list-style: none !important; padding-left: 25px !important; margin-bottom: 1em; counter-reset: list-item; } .gtr-container-xyz123 ol li { position: relative !important; padding-left: 25px !important; margin-bottom: 0.5em !important; font-size: 14px; counter-increment: none; list-style: none !important; } .gtr-container-xyz123 ol li::before { content: counter(list-item) "." !important; color: #0000FF !important; position: absolute !important; left: 0 !important; font-weight: bold !important; width: 20px !important; text-align: right !important; } @media (min-width: 768px) { .gtr-container-xyz123 { padding: 30px; } } Machine vision has the advantages of high speed, high precision, repeatability, objectivity, etc. After adding machine vision to automated equipment, its detection and assembly efficiency and accuracy will be significantly improved compared to manual work. The field of machine vision has now become one of the cutting-edge research hotspots. Edge detection is an essential part of machine vision and an important image preprocessing technology. Since edges are the result of discontinuous grayscale values, this discontinuity can often be easily detected by using derivatives. Generally, first-order and second-order derivatives are selected to detect edges. In machine vision inspection, this method is usually called edge detection local operator method. For the detection of image edges, the Canny algorithm is used to process and segment the image. The basic steps of the specific algorithm are as follows: machine vision edge detection Filtering: The edge detection algorithm is mainly based on the first-order and second-order derivatives of the image intensity, but the calculation of the derivatives is very sensitive to noise, so filters must be used to improve the performance of the edge detector related to noise. It should be noted that most filters also cause a loss of edge strength while reducing noise, so there is a trade-off between edge enhancement and noise reduction. Enhancement: The basis of edge enhancement is to determine the change value of the neighborhood intensity of each point in the image. The enhancement algorithm can highlight points with significant changes in neighborhood (or local) intensity values. Edge enhancement is generally accomplished by calculating gradient amplitude. Detection: There are many points in the image with relatively large gradient amplitudes, and these points are not all edges in specific application fields, so some method should be used to determine which points are edge points. The simplest edge detection criterion is the gradient amplitude threshold criterion. Positioning: If an application requires determining the edge position, the edge position can be estimated at sub-pixel resolution, and the edge orientation can also be estimated. In edge detection algorithms, the first three steps are very commonly used. This is because in most cases, the edge detector is only required to point out that the edge appears near a certain pixel in the image, but there is no need to point out the precise location or direction of the edge. These four steps are essential when using machine vision for dimensional measurement, especially the precise location and orientation of the edge. Machine vision inspection technology, with its powerful performance advantages, standardizes product quality, has fast inspection speed, reliable and stable inspection results and can be inspected for a long time, and is widely used in various fields.
A brief analysis of industrial robot visual positioning technology 2026-08-31 .gtr-container-f7e9d2 { font-family: Verdana, Helvetica, "Times New Roman", Arial, sans-serif; color: #333; line-height: 1.6; padding: 15px; box-sizing: border-box; max-width: 100%; overflow-x: hidden; } .gtr-container-f7e9d2 p { font-size: 14px; margin-bottom: 1em; text-align: left !important; } .gtr-container-f7e9d2 h2 { font-size: 18px; font-weight: bold; color: #0000FF; margin-top: 1.5em; margin-bottom: 0.8em; text-align: left; } .gtr-container-f7e9d2 ul { list-style: none !important; padding-left: 25px !important; margin-bottom: 1em; } .gtr-container-f7e9d2 ul li { position: relative !important; padding-left: 15px !important; margin-bottom: 0.5em !important; font-size: 14px !important; text-align: left !important; list-style: none !important; } .gtr-container-f7e9d2 ul li::before { content: "•" !important; color: #0000FF !important; position: absolute !important; left: 0 !important; font-size: 1.2em !important; line-height: 1 !important; } .gtr-container-f7e9d2 ol { list-style: none !important; padding-left: 25px !important; margin-bottom: 1em; } .gtr-container-f7e9d2 ol li { position: relative !important; padding-left: 25px !important; margin-bottom: 0.5em !important; font-size: 14px !important; text-align: left !important; list-style: none !important; } .gtr-container-f7e9d2 ol li::before { content: counter(list-item) "." !important; position: absolute !important; left: 0 !important; color: #0000FF !important; font-weight: bold !important; width: 20px !important; text-align: right !important; } .gtr-container-f7e9d2 img { max-width: 100%; height: auto; display: block; margin: 1em auto; } .gtr-container-f7e9d2 .image-caption { font-size: 12px; color: #666; text-align: center; margin-top: 0.5em; margin-bottom: 1.5em; } @media (min-width: 768px) { .gtr-container-f7e9d2 { padding: 25px 50px; } .gtr-container-f7e9d2 h2 { font-size: 20px; } } The robot integrates electronic technology, sensing technology and intelligent control technology. It is a machine device that can automatically perform work tasks. It can accept human command and can also act independently in accordance with the principles and programs formulated by artificial intelligence technology. It has been applied in many fields. At present, industrial robots can only perform predetermined instructions in a strictly defined structured environment and lack the ability to perceive and adapt to the environment, which greatly limits the application of robots. The workpiece visual positioning method, combined with special image processing software, uses the robot's visual control without the need to teach or offline program the industrial robot's motion trajectory in advance. It can achieve reliable positioning of the industrial robot visual system and play an active role in improving the workpiece positioning accuracy and processing effect. It can save a lot of programming time and improve production efficiency and processing quality. In China, this aspect is mainly used in tracking welding seams by welding robots. 1. Composition of visual positioning system The robot visual positioning system is composed of (as shown in the figure below). A spray tool and a single camera are installed at the end of the articulated robot so that the workpiece can completely appear in the camera's image. The system includes camera system and control system: Camera system: It consists of a single camera, computer and acquisition system (including image acquisition card), responsible for the acquisition of visual images and machine vision algorithms; it is recommended to use a digital camera for this system, and the extraction accuracy will be higher than that of a general camera. Control system: It consists of a computer and a control box and is used to control the actual position of the end of the robot; The work area is photographed by a CCD camera, and the computer extracts tracking features through image recognition methods for data recognition and calculation. 1578648768138220.jpg Figure 1 Composition of the visual positioning system of the spraying robot 2. Working principle of visual positioning system The American TEO brand digital camera TM-C6597E is used, equipped with a TM-C520HP image acquisition system. It is designed with a dedicated camera, balanced transmission line, and image acquisition card to input the video signal into the calculator and process it quickly. First, select a local image of the object being tracked. This step is equivalent to the process of offline learning, establishing a coordinate system in the image and training the system to find the tracking object. After learning, the image card continuously collects images, extracts tracking features, performs data identification and calculation, solves the given position values ​​of each joint of the robot through inverse kinematics, and finally controls the high-precision end actuator to adjust the robot's position. In this way, the visual positioning system combines area-based matching and shape feature recognition for data recognition and calculation, and can quickly and accurately identify the boundaries and centers of object features. The robot control system obtains the angle error of each joint position of the robot through inverse kinematics solution, and finally controls the high-precision end actuator to adjust the robot's posture to eliminate this error. This solves the problem that the actual position of the robot end is far from the desired position, and improves the positioning accuracy of traditional robots. 3. Image feature extraction The contrast between the workpiece on the workbench and the background of the workbench forms a big difference in color, that is, the workpiece is identified as black, and the center line of the black image is extracted. The acquisition system uses this information as an important feature for identifying the workpiece. When a general vision system acquires a workpiece image, it cannot be used directly in the vision system due to various conditions and noise interference. Image preprocessing such as grayscale correction and noise filtering must be performed through image analysis and recognition.
What are the advantages of USB industrial cameras? 2026-08-31 .gtr-container-xyz123 { font-family: Verdana, Helvetica, "Times New Roman", Arial, sans-serif; color: #333; line-height: 1.6; padding: 15px; font-size: 14px; } .gtr-container-xyz123 p { margin-bottom: 1em; text-align: left; font-size: 14px; } .gtr-container-xyz123 h2 { font-size: 18px; font-weight: bold; color: #0000FF; margin-top: 1.5em; margin-bottom: 0.8em; text-align: left; } .gtr-container-xyz123 h3 { font-size: 16px; font-weight: bold; color: #0000FF; margin-top: 1.2em; margin-bottom: 0.6em; text-align: left; } .gtr-container-xyz123 ul { list-style: none !important; padding-left: 20px !important; margin-bottom: 1em; } .gtr-container-xyz123 ul li { position: relative !important; padding-left: 15px !important; margin-bottom: 0.5em !important; font-size: 14px; list-style: none !important; } .gtr-container-xyz123 ul li::before { content: "•" !important; position: absolute !important; left: 0 !important; color: #0000FF !important; font-size: 1.2em !important; line-height: 1 !important; } .gtr-container-xyz123 ol { list-style: none !important; padding-left: 25px !important; margin-bottom: 1em; } .gtr-container-xyz123 ol li { position: relative !important; padding-left: 20px !important; margin-bottom: 0.5em !important; font-size: 14px; list-style: none !important; } .gtr-container-xyz123 ol li::before { content: counter(list-item) "." !important; position: absolute !important; left: 0 !important; color: #0000FF !important; font-weight: bold !important; width: 18px !important; text-align: right !important; } @media (min-width: 768px) { .gtr-container-xyz123 { padding: 25px; } } Among machine vision system components, industrial cameras can be said to be the "heart" of the system. Throughout the development of the industry, digital cameras have long been popular in the world. USB2.0 industrial cameras, 1394 industrial cameras and GigE industrial cameras have gradually replaced analog cameras as the mainstay and become the three mainstream digital cameras in the industrial camera market. In industry applications, USB industrial cameras are gradually showing their application strength and product charm, and will become the new overlord in the industrial camera market. USB industrial camera Cost advantages of USB industrial cameras: As the most widely used interface in the world, the USB interface has extremely cheap interface driver chips and driver circuits. The cost of a camera mainly consists of three parts: imaging chip and circuit, interface driver chip and circuit, and housing. The cost of the USB interface driver is much lower than that of the 1394 and GigE interface drivers. Therefore, the price of the USB industrial camera is not only cheaper than the original analog camera with an analog capture card, but also cheaper than the camera with the 1394 and GigE interface. The overall cost of USB industrial cameras (the camera itself and supporting cables) is 15%-30% lower than other digital cameras. Ease of use of USB industrial cameras: USB interface is the most widely used interface in the world. Various computers come with 2-4 USB interfaces. USB industrial cameras can be directly connected to the USB interfaces of these computers to work stably, while 1394 cameras require a separate 1394 capture card to be installed in the computer to work. In addition, the USB interface can directly power USB industrial cameras without the need to prepare a separate power supply for the camera, while GigE cameras require an independent power supply to power the camera separately. Therefore, the ease of use of USB industrial cameras is the best among the three digital cameras. The future continuous upgradeability of USB industrial cameras: As the most widely used interface in the world, USB interface is continuously promoted by world-class associations to upgrade the USB interface protocol. USB3.0 is becoming the standard interface for the new generation of computers and electronic products. At present, USB3.0 industrial cameras have come out. The transmission speed is 5X higher than USB2.0, reaching 2.5Gbit/s, which is 3 times the 1394B transmission speed and 2.5 times the GigE transmission speed. It will become the main interface for high-speed industrial applications in the next 2-3 years. USB industrial camera stability: USB industrial cameras are very suitable for applications where one computer is equipped with 1-2 cameras, and the stability is very good. USB industrial cameras are the best choice for most medium and low-speed industrial applications and can greatly save user costs. The above is an introduction to "What are the advantages of USB industrial cameras". Dior Technology's products cover industrial and medical machine vision systems and products, mainly including: a full range of industrial cameras, special cameras for industrial image measurement, special cross-line cameras for laser cutting, special image collectors for microscopic imaging, ultra-high-definition pathological microscopic imaging conference systems, pathological microscopic image analysis and remote consultation systems. Products are widely used in scientific research institutes, hospitals and schools, factories and mining enterprises, cultural relic appraisal units, criminal investigation and justice, intelligent transportation and other industries.
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