Novel Object Motion Estimation Method for Industrial Vision Systems

David Jenni^*
*Correspondence: David Jenni, Department of Civil Engineering, Cairo University, Giza, Egypt, Email:

Introduction

In many manufacturing processes, industrial vision systems are used to monitor manufacturing procedures. The adoption of industrial vision systems as a data acquisition measurement falls under the umbrella of the recently proposed concept of industrial information integration consequently, higher level intelligence such as control automation is anticipated. Aligning machines have used industrial vision systems to align objects. Vision systems can recognize and reject misaligned objects by working with a pneumatic device. A motion estimation method for industrial vision systems is required because alignment efficiency is dependent on the appropriate timing and pressure of the blown objects, as shown by their motion. This paper proposed a novel object motion estimation method based on the properties of industrial images, as opposed to the typical pre-prepared templates used by conventional motion estimation methods in this field. After initializing a bounding box for each object within a restricted observation area, motion estimation is carried out by updating the bounding box in accordance with the expectation–maximization principle. The results of our experiments showed that, in comparison to conventional template matching techniques, the proposed method was able to provide parts with robust and continuous motion estimation while also reducing processing time.

Discussion

Industrial vision systems are increasingly being used in manufacturing industries for process monitoring and quality control due to the prevalence of sensors and advancements in communication technologies. Industrial aligning machines, where misaligned objects are detected by industrial highspeed cameras and rejected by pneumatic devices to achieve alignment, have incorporated vision systems for this purpose. An example of this kind of alignment mechanism would be to align the orientation of electronic parts, which are light and need to be aligned because they need to be in a certain orientation for normal operation. An industrial vision system is used to demonstrate this electronic part alignment in Figure 1. The electronic components are moved forward by a slanting vibrating chute, as shown in the figure. In order to observe the orientations of the components, an industrial high-speed camera is installed obliquely. An air nozzle underneath the chute blows a part off the chute when the vision system detects that it is not oriented correctly. Note that the rejected parts are flipped down to the lower stage and realigned there because the chute is shaped like a staircase.

Support for actual physical systems is an important feature of IIIE.provide an illustration of how integrating information from multiple disciplines can simplify and enhance aircraft analysis. The process of integrating information is broken down into three main ideas in the paper: the physical field based on geometry, the field-state iteration, and pipeline operators. Physical parameters from various dimensional geometries are exchanged through deliberate interaction between these components, resulting in real-time multi-physical field coupling. In contrast, we propose a motion estimation technique that serves as a foundation for IIIE and can help industrial vision systems become more intelligent. More specifically, the information about a machine's motion that is gleaned from the proposed approach can easily be used as a guide for gaining a deeper comprehension of its operational state. Additionally, the estimated motion information can be used as a feedback signal for an algorithm like reinforcement learning in a control automation system that incorporates the extracted data [1-5].

Conclusion

The electronic components in this sample image are fed from left to right at a high density, and the air nozzle blows parts that are oriented incorrectly to realign them within the red dashed rectangle area. The blown settings have a significant impact on the alignment mechanism's efficiency and yield rates: timing of the blow and air pressure An object motion estimation method needs to be developed for industrial vision systems because the motion of the blown objects is causally influenced by the appropriateness of the blown settings. However, the wider field of industrial information integration engineering is involved when industrial vision systems are implemented. The theoretical and practical significance of the IIIE concept has steadily increased. The substantial theoretical advancements described in a previous work have had an impact on national strategies like industry 4.0 in Germany and the industrial internet consortium in the United States.

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