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Advanced Practical Course: Sensor-enabled Intelligent EnvironmentsBarcode-based Object Recognition Final Presentation Presented by: Nacer KHALIL Supervised by: Dejan PANGERCIC

Table of content I- Overall project goal II- Autofocus III- Bacode decoding IV- information retrieval V- Barcode localization VI- Conclusion

II-AutofocusHow autofocus works • Active vs passive autofocus Courtesy of howstuffworks.com

II-Autofocus(continued)

II- AutofocusImplementation in the project • Used camera: Logitech QC PRO 9000 • Driver used: ROS::uvc_camera • Problem: Autofocus is not supported by the driver • Solution: • Autofocus was added to uvc_camera driver • Autofocus algorithm was taken from GUVCVIEW software and integrated within uvc_camera driver

II- Autofocus result

III-Barcode decodingHow Zbar works Courtesy of Jeff Brown

IV-Information retrieval • Barcoo is a product information store that has a database composed of 7 million commercial objects. • Access to this database was granted to us. • Communication to the database is done through HTTP protocol. • Request: an http link containing the barcode • Response: XML file containing all information about the object http://www.barcoo.com

IV- Information retrieval Barcoo request response example • Request: • http://www.barcoo.com/api/get_product_complete? Pi=73705207908 &pins=ean&amp ;format=xml&source=ias-tum • Response: We are parsing for: - Image - product name - category - producer

V- Barcode localization Techniques used • Techniques used to find the barcode region of interest • Blob-based barcode localization • Parallel line-based localization • Adjacent line-based localization

V- Barcode localization Blob-based localization(working example)

V- Barcode localization Blob-based localization (not working example)

V- Barcode localization Adjacent line-based localization

V-Barcode localization How adjacent line-based localization works

V-Barcode localization Adjacent line-based approach explanation - Takepicture • Convert to grayscale • Parameters: interval size, min/max # of transitions, max Jeffrie’s value, min # of rows per ROI Image matrix Transitions matrix Eliminated intervals

V-Barcode localization Adjacent line-based approach explanation (continued) Jeffrie ’s distance matrix Eliminated intervals matrix Final matrix

IV- Barcode localization Adjacent line-based localization - results

Open Source Code Packages list: • zbar_barcode_reader_node • zbar_qt_ros • uvc_camera • barcode_detection Repositories: • http://code.cs.tum.edu/indefero/index.php//p/seie2011fall/source/tree/HEAD/khalil • http://code.cs.tum.edu/indefero/index.php//p/ias-perception/source/tree/master/

Conclusion • Project is composed of three parts: • Barcode localization • Implementation of autofocus • Information retrieval of objects • Future work: • Creation of the barcoo ontology and storage on KnowRob • Integration and testing on PR2 • Integration with object modeling center

Demonstrations of the project in the kitchen lab after the presentations end

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