Embedded Linux System for Digital Image Recognition using Internet of Things

The present paper describes the use of Digital Image Processing and Internet of Things for gestures recognition using depth sensors available on Kinect R © device. Using the open source libraries OpenCV and libfreenect, image data are translated and used for communicating Raspberry Pi embedded Linux system with PIC microcontroller board for peripheral devices controlling. LED is triggered according to the hand gesture representing the corresponding number. Data are stored in a PHP Apache server running locally on Raspberry Pi. The proposed system can be used as a multifunctional tool in areas such as learning process, post-traumatic rehabilitation and visual and motor cognition time. Using image binarization and Naive-Bayes classifier, the achieved results show error lower than 5%.

[1]  Oceans,et al.  Oceans engineering for today's technology and tomorrow's preservation : proceedings , 1994 .

[2]  W. Pieczynski,et al.  Adaptative segmentation of SAR images , 1994, Proceedings of OCEANS'94.

[3]  Gilberto Câmara,et al.  Spring: integrating remote sensing and gis by object-oriented data modelling , 1996, Comput. Graph..

[4]  Hugo Vieira Neto,et al.  Processamento digital de imagens , 1999 .

[5]  R. Deriche,et al.  A variational framework for active and adaptative segmentation of vector valued images , 2002, Workshop on Motion and Video Computing, 2002. Proceedings..

[6]  B. Schiele,et al.  Combined Object Categorization and Segmentation With an Implicit Shape Model , 2004 .

[7]  Y. LeCun,et al.  Learning methods for generic object recognition with invariance to pose and lighting , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[8]  Mohammed Bennamoun,et al.  Three-Dimensional Model-Based Object Recognition and Segmentation in Cluttered Scenes , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Antonio Criminisi,et al.  TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation , 2006, ECCV.

[10]  Adrian Kaehler,et al.  Learning opencv, 1st edition , 2008 .

[11]  Sandro César,et al.  SanUSB: software educacional para o ensino da tecnologia de microcontroladores SanUSB: educational software development for the mi crocontrollers technology education , 2009 .

[12]  Li Ma,et al.  Fast global segmentation based on the dual formulation of TV-norm , 2010, 2010 3rd International Congress on Image and Signal Processing.

[13]  Jidong Huang,et al.  Study on the use of Microsoft Kinect for robotics applications , 2012, Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium.

[14]  Renata Imaculada Soares Pereira,et al.  SanUSBee: Ferramenta para gravação wireless de microcontroladores via Bluetooth e Zigbee , 2012 .

[15]  Shao-Yi Chien,et al.  Perpetual video camera for Internet-of-things , 2012, 2012 Visual Communications and Image Processing.

[16]  Chun-Wei Tan,et al.  Efficient iris segmentation using Grow-Cut algorithm for remotely acquired iris images , 2012, 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[17]  Huini Du,et al.  An algorithm for automatic flood histogram segmentation for a PET detector , 2012, 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC).

[18]  T. V. Prabhakar,et al.  Infinite Coffee Cup , 2013, 2013 Texas Instruments India Educators' Conference.

[19]  Ghassan Hamarneh,et al.  Bounded Labeling Function for Global Segmentation of Multi-part Objects with Geometric Constraints , 2013, 2013 IEEE International Conference on Computer Vision.

[20]  Wei Miao,et al.  A power-constrained contrast enhancement algorithm for AMOLED display using histogram segmentation , 2013, 2013 IEEE 10th International Conference on ASIC.

[21]  Mengyin Fu,et al.  Object segmentation and recognition in 3D point cloud with language model , 2014, 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI).

[22]  Nirbhar Neogi,et al.  Defect detection of steel surface using entropy segmentation , 2014, 2014 Annual IEEE India Conference (INDICON).

[23]  Girma Tewolde,et al.  Design and implementation of vehicle tracking system using GPS/GSM/GPRS technology and smartphone application , 2014, 2014 IEEE World Forum on Internet of Things (WF-IoT).

[24]  Pramod Anantharam,et al.  Semantic Gateway as a Service Architecture for IoT Interoperability , 2014, 2015 IEEE International Conference on Mobile Services.

[25]  R. I. S. Pereira,et al.  Online Monitoring System for Electrical Microgeneration via Embedded WiFi Modem , 2016, IEEE Latin America Transactions.

[26]  Ravi Kishore Kodali,et al.  IoT based smart security and home automation system , 2016, 2016 International Conference on Computing, Communication and Automation (ICCCA).

[27]  Sandip Das,et al.  Home automation using Internet of Thing , 2016, 2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON).

[28]  Srivatsava Jandhyala,et al.  An Accurate All CMOS Temperature Sensor for IoT Applications , 2016, 2016 IEEE Computer Society Annual Symposium on VLSI (ISVLSI).

[29]  Jianning Liang,et al.  A Vision Based Method for Object Recognition , 2016, 2016 3rd International Conference on Information Science and Control Engineering (ICISCE).

[30]  Carlos Pereira,et al.  IoT interoperability for actuating applications through standardised M2M communications , 2016, 2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM).

[31]  Abba Suganda Girsang,et al.  Face recognition using eigenface with naive Bayes , 2016, 2016 11th International Conference on Knowledge, Information and Creativity Support Systems (KICSS).

[32]  Yon-Ping Chen,et al.  Real-time and low-memory multi-face detection system design based on naive Bayes classifier using FPGA , 2016, 2016 International Automatic Control Conference (CACS).

[33]  David E. Culler,et al.  Enabling Synergy in IoT: Platform to Service and Beyond , 2016, 2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI).

[34]  Sami Hyrynsalmi,et al.  Survey of prototyping solutions utilizing Raspberry Pi , 2017, 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[35]  Yoshua Bengio,et al.  The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[36]  Edward J. Delp,et al.  Nuclei Segmentation of Fluorescence Microscopy Images Using Three Dimensional Convolutional Neural Networks , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[37]  Vijanth Sagayan Asirvadam,et al.  A Review on Segmentation and Modeling of Cerebral Vasculature for Surgical Planning , 2017, IEEE Access.

[38]  Piyush Vyas,et al.  A robust technique for image processing based on interfacing of Raspberry-Pi and FPGA using IoT , 2017, 2017 International Conference on Computer, Communications and Electronics (Comptelix).

[39]  Ali Selman Aydin,et al.  CNN Based Yeast Cell Segmentation in Multi-modal Fluorescent Microscopy Data , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[40]  Caner Ozcan,et al.  Fast text classification with Naive Bayes method on Apache Spark , 2017, 2017 25th Signal Processing and Communications Applications Conference (SIU).

[41]  Shujuan Wang,et al.  Naive Bayes classifiers for music emotion classification based on lyrics , 2017, 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS).

[42]  Muhammad Imran Razzak,et al.  Microscopic Blood Smear Segmentation and Classification Using Deep Contour Aware CNN and Extreme Machine Learning , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[43]  Pabitra Mitra,et al.  Generative Adversarial Learning for Reducing Manual Annotation in Semantic Segmentation on Large Scale Miscroscopy Images: Automated Vessel Segmentation in Retinal Fundus Image as Test Case , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[44]  Jaime Lloret,et al.  An IoT service-oriented system for agriculture monitoring , 2017, 2017 IEEE International Conference on Communications (ICC).

[45]  Renata Imaculada Soares Pereira,et al.  Embedded Linux System for Digital Image Recognition using Internet of Things , 2018 .