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39 Experiments with Raspberry Pi and Arduino This book is about Raspberry Pi 3 and Arduino camera projects. The book explains in simple terms and with tested and working example projects, how to configure and use a Raspberry Pi camera and USB based webcam in camera-based projects using a Raspberry Pi. Example projects are given to capture images, create timelapse photography, record video, use the camera and Raspberry Pi in security and surveillance applications, post images to Twitter, record wildlife, stream live video to YouTube, use a night camera, send pictures to smartphones, face and eye detection, colour and shape recognition, number plate recognition, barcode recognition and many more. Installation and use of popular image processing libraries and software including OpenCV, SimpleCV, and OpenALPR are explained in detail using a Raspberry Pi. The book also explains in detail how to use a camera on an Arduino development board to capture images and then save them on a microSD card. All projects given in this book have been fully tested and are working. Program listings for all Raspberry Pi and Arduino projects used in this book are available for download on the Elektor website.

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This camera module adopts a SmartSens SC3336 sensor chip with 3 MP resolution. It features high sensitivity, high SNR, and low light performance and it is capable of a more delicate and vivid night vision imaging effect, and can better adapt to ambient light changes. Also, it is compatible with Luckfox Pico series boards. Specifications Sensor Sensor: SC3336 CMOS size: 1/2.8" Pixels: 3 MP Static resolution: 2304x1296 Maximum video frame rate: 30fps Shutter: Rolling shutter Lens Focal length: 3.95 mm Aperture: F2.0 FOV: 98.3° (diagonal) Distortion: <33% Focusing: Manual focus Downloads Wiki

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Raspberry Pi 5 provides two four-lane MIPI connectors, each of which can support either a camera or a display. These connectors use the same 22-way, 0.5 mm-pitch “mini” FPC format as the Compute Module Development Kit, and require adapter cables to connect to the 15-way, 1 mm-pitch “standard” format connectors on current Raspbery Pi camera and display products.These mini-to-standard adapter cables for cameras and displays (note that a camera cable should not be used with a display, and vice versa) are available in 200 mm, 300 mm and 500 mm lengths.

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Raspberry Pi 5 provides two four-lane MIPI connectors, each of which can support either a camera or a display. These connectors use the same 22-way, 0.5 mm-pitch “mini” FPC format as the Compute Module Development Kit, and require adapter cables to connect to the 15-way, 1 mm-pitch “standard” format connectors on current Raspbery Pi camera and display products.These mini-to-standard adapter cables for cameras and displays (note that a camera cable should not be used with a display, and vice versa) are available in 200 mm, 300 mm and 500 mm lengths.

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Raspberry Pi 5 provides two four-lane MIPI connectors, each of which can support either a camera or a display. These connectors use the same 22-way, 0.5 mm-pitch “mini” FPC format as the Compute Module Development Kit, and require adapter cables to connect to the 15-way, 1 mm-pitch “standard” format connectors on current Raspbery Pi camera and display products.These mini-to-standard adapter cables for cameras and displays (note that a camera cable should not be used with a display, and vice versa) are available in 200 mm, 300 mm and 500 mm lengths.

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OV7740 is a AI Camera powered by Kendryte K210, an edge computing system-on-chip(SoC) with a dual-core 64bit RISC-V CPU and state-of-art neural network processor. Features Dual-Core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal) Dual Independent Double Precision FPU 8MiB 64bit width On-Chip SRAM Neural Network Processor(KPU) / 0.8Tops Field-Programmable IO Array (FPIOA) AES, SHA256 Accelerator Direct Memory Access Controller (DMAC) Micropython Support Firmware encryption support On-board Hardware: Flash: 16M Camera :OV7740 2x Buttons Status Indicator LED External storage: TF card/Micro SD Interface: HY2.0/compatible GROVE Applications Face recognition/detection Object detection/classification Obtain the size and coordinates of the target in real-time Obtain the type of detected target in real-time Shape recognition Video recorder Included 1x UNIT-V(include 20cm 4P cable and USB-C cable)

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THSER102 is a plug-and-play cable extension kit for Raspberry Pi Camera Modules. The kit is compatible with Raspberry Pi Camera Module 3, in addition to Camera V2 (version 2.1), HQ/Global Shutter Camera, and defined modes of the Raspberry Pi Camera Module V1.3. The THSER102 extends the cable length for >10 meters between the Raspberry Pi Camera Module and the Computer with a standard LAN Cable. There is no need for software or coding. THSER102 works as if the Raspberry Pi Camera were directly connected to the computer. The THSER102 also supports advanced applications. HAT on HAT support allows to use another HAT board on top of THSER102 Rx Board. 3ch GPIO Extension allows extending GPIO communication between the camera location and the computer. Features Supporting all Raspberry Pi Camera Modules including Camera Module 3 >10-meter Cable Extension Plug and Play No software configuration is needed. Camera works as if THSER102 not exists. Advanced Applications Supported HAT on HAT 3ch GPIO Extension Included 1x Tx Board 1x Rx Board 1x LAN Cable (2 m) 2x Flat Flex Cables 1x Pin Header 6x Mounting Screws for Rx Board 3x Longer Spacers for Rx Board 4x Mounting screws for Tx Board (for Camera V2 only) 4x Shorter Spacers for Tx Board (for Camera V2 only) 4x Mounting Nuts for Tx Board (for Camera V2 only) Downloads Datasheet

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Is your house haunted? Or, rather, are you convinced that your house is haunted but have never been able to prove it since you've never had a camera that integrated with your Raspberry Pi Zero but was still small enough that the ghosts wouldn't notice it? Luckily, the spy camera for Raspberry Pi Zero is smaller than a thumbnail with a high enough resolution to see people, ghosts, or whatever it is you're looking for. It's about the size of a cell phone camera – the module being just 8.6 x 8.6 mm – with only a 2' cable, so you can create an extra compact and sneaky little spy cam. It has a 160-degree focal angle for a very wide/distorted fisheye effect that's great for security systems or watching a big swath of the living room or roadway. Like the Raspberry Pi camera board, it attaches to your Raspberry Pi Zero v1.3 or Zero W by way of the small socket on the board's edge closest to the 'PWR in' port. This interface uses the dedicated CSI interface, which was designed especially for interfacing to cameras. The CSI bus is capable of extremely high data rates, and it exclusively carries pixel data. The camera is connected to the BCM2835 processor on the RPi via the CSI bus, a higher bandwidth link which carries pixel data from the camera back to the processor. This bus travels along the ribbon cable that attaches the camera board to the Pi. The ribbon cables are compatible with both the RPi Zero v1.3 and RPi Zero W. The sensor itself has a native resolution of 5 megapixels and has a fixed focus lens onboard. It has similar specs as the original RPi camera, but is not as high-res as the new RPi camera v2! Specifications Camera Module Dimensions: 8.6 x 8.6 mm Lens Diameter: 10 mm Total Length: 60 mm Lens Focal Angle: 160 degrees Weight: 1.9 g

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The M12 Mount Lens (12 MP, 8 mm) is ideal for use with the Raspberry Pi HQ Camera Module, offering sharp and detailed imaging for a wide range of applications.

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Computer vision is probably the most exciting branch of image processing, and the number of applications in robotics, automation technology and quality control is constantly increasing. Unfortunately entering this research area is, as yet, not simple. Those who are interested must first go through a lot of books, publications and software libraries. With this book, however, the first step is easy. The theoretically founded content is understandable and is supplemented by many practical examples. Source code is provided with the specially developed platform-independent open source library IVT in the programming language C/C++. The use of the IVT is not necessary, but it does make for a much easier entry and allows first developments to be quickly produced. The authorship is made up of research assistants of the chair of Professor Ruediger Dillmann at the Institut für Technische Informatik (ITEC), Universitaet Karlsruhe (TH). Having gained extensive experience in image processing in many research and industrial projects, they are now passing this knowledge on. Among other subjects, the following are dealt with in the fundamentals section of the book: Lighting, optics, camera technology, transfer standards, camera calibration, image enhancement, segmentation, filters, correlation and stereo vision. The practical section provides the efficient implementation of the algorithms, followed by many interesting applications such as interior surveillance, bar code scanning, object recognition, 3-D scanning, 3-D tracking, a stereo camera system and much more.

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