機器視覺的智能圖像處理技術雖然目前還處於發展中階段，但仍存在不少技術上的瓶頸。那麼，到底哪些問題阻擋了機器視覺系統的發展呢?

目前機器視覺系統的技術問題：

1.穩定性：雖然機器視覺系統目前在研究和開發中表現良好，但在複雜多變的應用環境中仍是不是出現問題。

2.實時性：圖像採集和處理速度較慢，一旦引入更深度的學習類算法和加大系統實施處理的難度，會跟不上機器運行和控制的節奏。

3.準確性：機器視覺系統要求圖像識別和測量準確性接近100%，任何微小偏差都會帶來難以估計的後果。

4.系統能力：嵌入式圖像處理系統無法滿足運算量較大的圖像處理運算。

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Current machine vision system technical issues:

1. Stability: Although machine vision systems currently perform well in research and development, they are still not a problem in a complex and changing application environment.

2. Real-time performance: The image acquisition and processing speed is slow. once a deeper learning algorithm is introduced and the system is more difficult to implement, it will not keep up with the rhythm of machine operation and control.

3. Accuracy: The machine vision system requires that the image recognition and measurement accuracy be close to 100%, and any slight deviation will bring incalculable consequences.

4. System Capabilities: The embedded image processing system can not meet the large amount of image processing operations.

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