With the increasing awareness of environmental protection and the development of circular economy, automatic beverage bottle recycling machines are gradually becoming a standard in public places. In order to improve recycling efficiency, reduce manual intervention, and ensure accurate classification and handling of various beverage bottles, beer bottles, etc., manufacturers need to install a dynamic barcode recognition system at the entrance of the automatic beverage bottle recycling machine.

In this issue, Xiao Ming will share with you the non-standard visual solutions provided by Akusense for such application scenarios

1. 360 ° dynamic recognition is required: the installation port is circular, and the code reading system needs to have all-round recognition capability, so that the barcode can be accurately recognized no matter which direction the bottle enters the recycling machine.

2. High speed detection: The system is required to be able to detect 40 bottles per minute, ensuring stable recognition even when the bottles are quickly thrown in.

3. Multi type barcode recognition: The system needs to be able to recognize barcodes of various sizes, colors, directions, and contaminants, including horizontal and vertical codes, as well as barcodes with stains and wrinkles.

4. High stability: Ensure stable operation of the system under various environmental conditions, such as changes in light, vibration, etc.

Hardware configuration:

1. 120 frame camera * 6: Choose a high frame rate camera to ensure fast capture of bottle dynamic images and improve recognition speed.

2. External light source: Design a circular external light source to ensure uniform illumination of all surfaces of the bottle and improve image quality.

3. Circular installation: Install 6 cameras and external light sources in a circular manner at the entrance of the bottle to achieve 360 ° coverage without dead corners.

Software algorithm:

1. Image preprocessing: Performing preprocessing operations such as denoising and contrast enhancement on captured images to improve barcode recognition rate.

2. Barcode detection: Advanced barcode detection algorithms are used to accurately identify barcodes of various types, sizes, and colors.

3. Multi camera collaboration: Develop a multi camera collaboration algorithm to ensure that six cameras can work simultaneously and quickly and accurately identify barcodes on bottles.

System optimization:

1. Real time optimization: Optimize the algorithm in real-time to ensure that the system can complete barcode recognition tasks in a very short amount of time.

2. Stability testing: Conduct system stability testing under various environmental conditions to ensure stable operation of the system.

1. Recognition speed: The system has successfully achieved the goal of detecting 40 bottles per minute, and can stably recognize barcodes even when bottles are quickly thrown in.

2. Recognition accuracy: The system can accurately recognize barcodes of various types, sizes, and colors, including those with stains and wrinkles, with a recognition accuracy rate of over 99%.

3. Stability: The system can operate stably under various environmental conditions, meeting the actual needs of customers.