PARKVI GMBH
- Address:
-
Am Mittleren Moos 48
Augsburg
86167
Germany
- Telephone:
- +49 8216 5072 933
- Website
-
https://parkvi.de/en/
- Email:
- info@parkvi.de
- Membership:
- UKIVA
Offering End-to-End Machine vision Systems
PARKVI provides Machine vision systems for manufacturing giants like BMW, Audi, AGCO(Fendt), Forvia, Procter & Gamble, and Bosch. Its offerings are industry-agnostic, serving production-based companies like automotive, e-mobility, battery and fuel cell production, packaging, food processing, photovoltaics, tire manufacturing, and pharmaceuticals. Catering to their dynamic machine vision needs, it offers end-to-end, bespoke, and cost-efficient image-processing solutions. This helps them achieve excellence in manufacturing management, inspection and defect detection, quality assurance, and process control.
PARKVI’s portfolio encompasses 2D, 3D, and line scan cameras, offering everything from conventional image processing to AI-based. Clients can also engage with the company for manufacturer-independent image processing consultation and procuring top-notch machine vision components like cameras, complex PC systems for vision, 3D vision sensors, and industrial code readers.
Products Supplied
- AI based Automated Inspection Weld seam inspection:
- We are your partner for system solutions for automatic weld seam inspections. We guarantee reliable and reproducible measurement and testing of all common welding and brazing processes.
Some defects that can be detected from a weld seam inspection are:
- Cracks in or next to the seam
- Arc strikes next to the seam
- Spatter
- Unfilled end craters
- Faulty weld toe
- Undercuts on both sides of the root
- Undercuts on both sides at the top of the seam
- Excessive sink marks in the welding seam
- Faulty weld pattern (rippling pitch ratio)
- Discoloration in the welding area
- Pores on the surface - 2D and 3D Surface inspection:
- Surface defects generally include defects of any kind that occur on the surface of workpieces. A distinction is made between functional and non-functional surface defects. The software differentiates between these defects and evaluates them. Surface defects include blowholes and pores, scratches, edge chipping, burrs, grooves, dents, notches or impact marks and ejection errors. The spectrum of Surface Inspection ranges from simple automatic inspection machines with manual loading and unloading to parameterizable category division and automatic palletizing and depalletizing.
- Deep learning based OCR detection:
- Optical character recognition using deep learning is a popular approach that involves training a neural network to recognize and extract text from images.
Employing deep learning and OCR entails following three steps:
Image pre-processing: The quality of the image is enhanced, meaning the image is skewed, the noise is removed and lighting adjusted. This first step is essential to create the best environment for the data to be extracted.
Text detection: To locate the text within a document, several models can be used. They create bounding boxes over each text identified in the image or document. It is a preparatory step for data extraction.
Text recognition: After the text is located in the file, each bounding box is sent to the text recognition model. The final output of these models is the extracted text from the documents.
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