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BestsellerE-book
Author Davies, E. R. (E. Roy)

Title Image processing for the food industry [electronic resource] / E.R. Davies.

Imprint Singapore ; River Edge, NJ : World Scientific, ©2000.

Item Status

Description 1 online resource (xx, 289 pages) : illustrations.
Series Series in machine perception and artificial intelligence ; vol. 37
Series in machine perception and artificial intelligence ; vol. 37.
Bibliography Includes bibliographical references (pages 257-273) and indexes.
Contents Ch. 1. Introduction. 1.1. Food and its production. 1.2. Image processing and machine vision. 1.3. Biological versus machine vision. 1.4. How can image processing help with food processing? 1.5. The following chapters -- pt. 1. Image processing methodology. ch. 2. Images and image processing. 2.1. Introduction. 2.2. Images. 2.3. Image processing. 2.4. Median and rank-order filters. 2.5. Thresholding. 2.6. Adaptive thresholding. 2.7. Edge detection. 2.8. Concluding remarks -- ch. 3. Shape analysis. 3.1. Introduction. 3.2. Connected components analysis of images. 3.3. Skeletons and thinning. 3.4. Skeleton-based analysis of shape. 3.5. Distance functions. 3.6. General dilation and erosion operators. 3.7. Properties of dilation and erosion operators. 3.8. Closing and opening. 3.9. Summary of morphological operations. 3.10. Boundary pattern analysis. 3.11. Concluding remarks -- ch. 4. Feature detection and object location. 4.1. Introduction. 4.2. From template matching to inference. 4.3. Finding features. 4.4. Line location. 4.5. Circle location. 4.6. Ellipse location. 4.7. Graph matching. 4.8. Using the Hough transform for point pattern matching. 4.9. Concluding remarks -- ch. 5. Texture. 5.1. Introduction. 5.2. Tackling the problem of texture analysis. 5.3. Laws' approach. 5.4. Ade's approach. 5.5. Concluding remarks -- ch. 6. Three-dimensional processing. 6.1. Introduction. 6.2. Stereo vision. 6.3. Shape from shading. 6.4. Views and projections. 6.5. Motion. 6.6. Concluding remarks -- ch. 7. Pattern recognition. 7.1. Introduction. 7.2. Bayes' approach to SPR. 7.3. The nearest neighbour approach. 7.4. Artificial neural networks. 7.5. Supervised and unsupervised learning. 7.6. Principal components analysis. 7.7. Concluding remarks.
pt. 2. Application to food production. ch. 8. Inspection and inspection procedures. 8.1. Introduction. 8.2. Phases in the inspection process. 8.3. Details of the inspection process. 8.4. Lighting schemes. 8.5. Concluding remarks -- ch. 9. Inspection of baked products. 9.1. Introduction. 9.2. A basic case study: Jaffacake inspection. 9.3. Case study: inspection of cream biscuits. 9.4. Short case studies of baked product inspection. 9.5. Concluding remarks -- ch. 10. Cereal grain inspection. 10.1. Introduction. 10.2. Case study: location of dark contaminants in cereals. 10.3. Case study: location of insects. 10.4. Case study: high speed grain location. 10.5. Short case studies of grain and nut inspection. 10.6. Concluding remarks -- ch. 11. X-ray inspection. 11.1. Introduction. 11.2. X-ray image acquisition. 11.3. Case study: reliable thresholding of x-ray images. 11.4. Case study: inspection of frozen food packs. 11.5. Case study: design of hardware for inspection of frozen food packs. 11.6. Short case studies of x-ray inspection. 11.7. Concluding remarks -- ch. 12. Image processing in agriculture. 12.1. Introduction. 12.2. Case study: guidance of a crop-spraying vehicle. 12.3. Case study: model-based tracking of animals. 12.4. Case study: inspection and grading of potatoes. 12.5. Case study: inspection of apples. 12.6. Case study: inspection and grading of mushrooms. 12.7. Concluding remarks -- ch. 13. Vision for fish and meat processing. 13.1. Introduction. 13.2. Case study: species sorting of fish. 13.3. Case study: grading of prawns. 13.4. The problem of meat processing. 13.5. Case study: inspection and grading of poultry parts. 13.6. Concluding remarks -- ch. 14. System design considerations. 14.1. Introduction. 14.2. Design of inspection systems -- the status quo. 14.3. System optimization. 14.4. The value of case studies. 14.5. The way to go. 14.6. Further considerations relating to hardware accelerators. 14.7. The need for rigorous timing analysis of vision algorithms. 14.8. Concluding remarks -- ch. 15. Food processing for the Millennium. 15.1. Introduction. 15.2. The range of the case studies. 15.3. The cost of vision hardware. 15.4. The potential range of applications of vision. 15.5. Prognosis.
Summary This monograph provides detailed background on the image processing problems encountered in the food industry when automatic control and inspection systems are being designed and installed. It starts with a careful study of image processing and machine vision methodology, and then goes on to analyse how this can be applied in the main areas of food processing and production. A case study approach is used to give relevance to the work, making the book user-friendly. This book will help the food industry to observe 'due diligence', and researchers to be more aware of the problems of analysing images of food products.
Local Note eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America
Subject Food industry and trade -- Quality control.
Food adulteration and inspection -- Equipment and supplies.
Image processing -- Methodology.
Imaging systems -- Design and construction.
Radiography, Industrial.
Food processing plants -- Equipment and supplies.
Genre/Form Electronic books.
Other Form: Print version: Davies, E.R. (E. Roy). Image processing for the food industry. Singapore ; River Edge, NJ : World Scientific, ©2000 9810240228 (DLC) 2005297835 (OCoLC)44998979
ISBN 9789812797636 (electronic bk.)
9812797637 (electronic bk.)
9810240228
9789810240226