Optics and artificial vision. ([2021])

• Record Type: Book
• Further Information: Note: Rafael G. González-Acuäna, Héctor A. Chaparro-Romo, Israel Melendez-Montoya.
• Authors: González-Acuäna, Rafael G; Chaparro-Romo, Héctor A; Melendez-Montoya, Israel
• Other Names: Institute of Physics (Great Britain), publisher.
• Contents: 1. Optics, sensors and images -- 1.1. Introduction -- 1.2. Optics and images -- 1.3. Vision -- 1.4. Optical instruments and optical design -- 1.5. Cameras -- 1.6. CCD sensor -- 1.7. CMOS sensor -- 1.8. Python as a program language for this book -- 1.9. Artificial vision and computer vision -- 1.10. End notes 2. Introduction to computer vision -- 2.1. Loading and saving images -- 2.2. Image basics -- 2.3. Colour spaces -- 2.4. Basic image processing -- 2.5. Resizing images -- 2.6. Kernels and morphological operations -- 2.7. Blurring -- 2.8. Thresholding -- 2.9. Gradients and edge detection -- 2.10. Histograms -- 2.11. End notes 3. Optical flow -- 3.1. Introduction -- 3.2. The Lucas-Kanade algorithm -- 3.3. Application of the Lucas-Kanade algorithm and its Python code -- 3.4. The optical flow model -- 3.5. The Horn-Schunck algorithm -- 3.6. End notes 4. Object detection algorithms -- 4.1. Object detection -- 4.2. Sliding windows and image pyramids -- 4.3. The histogram of oriented gradients descriptor -- 4.4. Support vector machine -- 4.5. End notes 5. Image descriptors -- 5.1. Introduction to image descriptors -- 5.2. Basic statistics -- 5.3. Hu moments -- 5.4. Zernike moments -- 5.5. Haralick features -- 5.6. Local binary patterns -- 5.7. Keypoint detectors -- 5.8. Local invariant descriptors -- 5.9. Binary descriptors -- 5.10. End notes 6. Neural networks -- 6.1. Introduction -- 6.2. Neural networks in a nutshell -- 6.3. Single perceptron learning -- 6.4. Multilayer perceptrons -- 6.5. Convolutional neural networks -- 6.6. Metrics -- 6.7. CNN architectures -- 6.8. Transfer learning -- 6.9. End notes 7. Optical character recognition -- 7.1. Introduction -- 7.2. Problems in classical OCR -- 7.3. The basic scheme of a classical OCR algorithm -- 7.4. Classical OCR using machine learning -- 7.5. Modern OCR with deep learning -- 7.6. OCR with Tesseract -- 7.7. End notes 8. Facial recognition -- 8.1. Introduction to facial recognition -- 8.2. Local binary patterns for facial recognition -- 8.3. The eigenfaces algorithm -- 8.4. Example using the CALTECH faces dataset -- 8.5. A LBP face recognizer for your own face -- 8.6. Deep learning facial recognition -- 8.7. End notes 9. Artificial vision case studies -- 9.1. Measuring the camera-object distance -- 9.2. Single image depth estimation -- 9.3. State-of-the-art real-time facial detection -- 9.4. Fruit classification -- 9.5. End notes.
• Publisher Details: Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing
• Publication Date: 2021
• Extent: 1 online resource (various pagings), illustrations (some color)
• Subjects: 006.37; Computer vision; Optical physics; Optics and photonics; Computer vision
• Languages: English
• ISBNs: 9780750337076; 0750337079; 9780750337069; 0750337060
• Related ISBNs: 9780750337052; 9780750337083
• Notes: Note: Includes bibliographical references.; Note: Title from PDF title page (viewed on October 9, 2021).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.