How To Use Machine Vision To Calculate Palletized Boxes In A Warehouse

Despite the boom in science and technology sector many warehouses and wholesale distributors still have laborers in-charge of the redundant and dull tasks, which could easily be automated. This makes making mistakes highly likely. What if you had machines with image analysis ability handle some of those tasks for you?  

Let’s talk about this some more, but first why don’t you glance over these articles about programming languages for cloud enterprise development and best software outsourcing destinations

Well-known companies like Amazon and Quite Logistics are ahead of others in this industry and have employed robots to handle their warehouses. But others are only now starting to look closely at the task automation solutions. 

Managing large warehouses can be quite burdensome and hectic, hence, using machines to help run them is very appealing. Humans manually handling all the work can get tired and make mistakes. Each mistake equals to loss of time, money and resources. This is something everyone wants to avoid. If you install a machine with camera that is equipped with image analysis software then you won’t have to rely on your human operators who are prone to making errors. 

When programmed accurately, machines can be quite quick and efficient. The machine will receive instruction from you about the job it needs to do. However, the image that it will analyze must be of high quality. 

Machine Vision Solution

One of the most common task in warehouses is counting boxes stacked on a pallet. So, the image analysis strategy would be to include multiple iterations of image segmentation in this case. This first thing it would do is to separate the pallet from the boxes and other things in the surrounding.

Click hare : topportal

Click hare : f95zone

The second thing would be to separate each box from the other and things in its surroundings. For this purpose the machine needs to identify edges of the box and so that there are no mistakes. 

Neural Network

There are algorithms, which alone or in combination are used for identifying the edges of the boxes and other materials accurately. They are used as layers of convolution neural network also called CNN which are famously used in data analysis and classification. It is especially useful in image analysis. 

Neural networks are trained with multiple images of what they are to interpret in the future. The machine learns a pattern of the features of the images which helps it recognize it in the surroundings. In order to make the prediction of the neural network as accurate as that of a human’s it needs to see and learn from thousands of images. How can you know best CartonCloud.

Calculating the Boxes Using Volume

You can also allow the machine to use volume to find out the number of boxes that are loaded on the pallet. To find the number of boxes, the machine will require the volume of entire pallet, volume of all the boxes and volume of the single box. The machine uses a stereo camera and infrared proximity sensors to calculate things.  

Weaknesses of Image Analysis Software

Not all warehouses are perfectly organized for the algorithms to do their job. The following challenges can influence performance of the image analysis software. 

  • Boxes stacked in wrong order
  • Insufficient illumination
  • Shadows
  • Reflection of light from wrapping films
  • Variation in shapes and sizes of boxes

Final Words

If you are thinking about investing in automation in warehouse then machine vision may bring you good return on it. But to really earn profit, you must pay attention to your palletizing operations for improved efficiency. Keep your warehouses up with the standards, only then can image analysis algorithm perform to its full efficiency.