Exploring solutions for OCR recognition of smartphone charging heads in the 3C industry

Text is one of the most important sources of information for human beings, and natural scenes are full of all kinds of text symbols.

The industrial scene of the image text recognition is more complex, OCR appears in many different occasions, on some special surfaces, the product as a whole on the optical recognition of the characters, to facilitate information comparison and character printing error correction, to provide data support for the production: when detecting the character leakage of the spray code, the lack of spray code, the data is incorrect and so on, the system sends out a signal to the rejection device rejection processing or alarm tips.

AKUSENSE Solution

12 million color roll camera CA-C120R-E + 16mm fixed focus lens DA-1623014-10M + white shadowless bar light source.

1. Adopting high-precision positioning algorithm to provide accurate positional coordinates for subsequent screen printing inspection

2. Detecting character defects through differential algorithms to ensure the integrity of characters and other information and the appearance of defects

3. Using deep learning algorithm, OCR recognizes the character information on the surface, with an accuracy rate of >99.5%.

Specific application process

OCR recognition technology mainly relies on image processing and pattern recognition algorithms, by capturing the characteristics of the characters in the document, such as strokes, shape, size, spacing, etc., and comparing them with the preset character library, so as to identify the corresponding text information. Need to go through the following processes:

1. image acquisition

Use a high-resolution industrial camera or smartphone camera to capture images of the charging head.

Need to ensure that the shooting environment lighting is uniform, the charging head surface is clean and unobstructed.

2. Image pre-processing

Pre-processing operations such as binarization, denoising, contrast enhancement, etc. are performed on the captured image to improve the accuracy of subsequent recognition.

Image preprocessing can be realized through software algorithms or image processing libraries (such as OpenCV).

3. Regional localization

Through template matching, edge detection and other algorithms to locate the charging head needs to recognize the character or logo where the region. This step ensures the accuracy of subsequent OCR recognition and reduces unnecessary calculations.

4. OCR recognition

Character recognition is performed on the localized area. Characters can be converted to editable and searchable text based on the pixel information in the image.

5. Results Output

The results of OCR recognition are output as text, which can be saved to a database, file or displayed on the user interface. At the same time, the recognition results can be verified and calibrated to ensure the accuracy and reliability of the data.