{"product_id":"raspberry-pi-image-processing-programming-with-numpy-scipy-matplotlib-and-opencv-9781484282694","title":"Raspberry Pi Image Processing Programming: With Numpy, Scipy, Matplotlib and Opencv","description":"Chapter 1: Introduction to Single Board Computers and RPiChapter Goal: Brief intro into SBCs and RPiNo of pages Sub -Topics1. SBCs2. Raspberry Pi3. Raspberry Pi Imager and setup4. Configuring the Pi\u003cbr\u003eChapter 2: Introduction to Python and Digital Image ProcessingChapter Goal: Brief acquaintance with the subject of the bookNo of pages: Sub - Topics: 1. History of Python2. Features3. Installation of Python on Raspberry Pi4. IDEs for Python5. Digital Image Processing\u003cbr\u003eChapter 3: Getting Started with Image ProcessingChapter Goal: Getting to understand the basicsNo of pages: Sub - Topics: 1. Image Sources (Standard Image Datasets)2. Various Cameras for RPi3. Pillow Basics4. Tk Basics5. Reading and displaying images with Pillow and Tk6. Image Properties\u003cbr\u003eChapter 4: Basic Operations on ImagesChapter Goal: Getting to know PillowNo of pages: Sub - Topics: 1. Image modulea) Image channelsb) Mode Conversionc) Blendingd) Resizinge) Rotationf) Crop and pasteg) Alpha compositionh) Mandelbrot seti) Noise and gradient2. ImageChops module3. ImageOps module\u003cbr\u003eChapter 5: Advanced Operations on ImagesChapter Goal: Filtering and Enhancements 1. Image filter (will cover more filters in the second edition)2. Image enhancements (will cover additional effects)3. Color quantization4. Histogram and equalization\u003cbr\u003eChapter 6: Scientific Python\u003cbr\u003eChapter Goal: Introduction to the Scientific Python1. The SciPy stack2. NumPy, SciPy, and Matplotlib3. Image Processing with NumPy and Matplotlib\u003cbr\u003eChapter 7: Transformations, Interpolation, and Measurements Chapter Goal: Transformations and Measurements1. Transformations and Interpolationsa) Affine_transformb) Geometric_transformc) Map_coordinatesd) Rotatee) Shiftf) Spline_filterg) Spline_filter1dh) Zoom2. Measurementsa) Center_of_massb) Extremac) Find_objectsd) Histograme) Labelf) Labeled_comprehensiong) Maximumh) Maximum_positioni) Meanj) Mediank) Minimuml) Minimum_positionm) Standard_deviationn) Sum_labelso) Variancep) Watershed_ift\u003cbr\u003eChapter 8: Filters and their ApplicationChapter Goal: Study Various types of filters1. Kernels, Convolution, Filters 2. Correlation3. Low Pass Filtersa) Blurring Filter (Gaussian, Gaussian 1D, uniform, uniform 1D, percentile, rank)b) Noise Removal (Gaussian, Median, Maximum, Minimum, rank)4. High Pass filtersa) Prewittb) Sobelc) Laplaciand) Gaussian Gradient Magnitudee) Gaussian Laplace5. Fourier Filters\u003cbr\u003eChapter 9: Morphology, Thresholding, and SegmentationChapter Goal: Study operations1. Morphologya) Distance transformb) Structuring Element (generate_binary_structure)c) Binary Morphological Operationsd) Greyscale Morphological Operations\u003cbr\u003ee) More Morphological Operations2. Thresholding and Segmentation \u003cp\u003e\u003c\/p\u003eChapter 10: pgmagik\u003cbr\u003e\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Apress\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 07\/06\/2022\u003cbr\u003e\u003cb\u003eISBN:\u003c\/b\u003e 9781484282694\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 140\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.82lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.21h x 6.14w x 0.55d","brand":"Ashwin Pajankar","offers":[{"title":"Default Title","offer_id":42362332676277,"sku":"9781484282694","price":46.74,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0473\/0804\/6492\/products\/img_cc1632dc-90cc-4c38-b7c6-e493ff12a9ce.jpg?v=1662434385","url":"https:\/\/pastforward.org\/products\/raspberry-pi-image-processing-programming-with-numpy-scipy-matplotlib-and-opencv-9781484282694","provider":"Past Forward","version":"1.0","type":"link"}