Image Processing in agro-based industries
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Image processing techniques are used in agro-based industries for quality control, product grading, and automation of tasks like packaging inspection and labeling. Key applications of image processing include examining visual features like color, texture, size, and shape to evaluate physical properties of food. While current systems are successful under constrained conditions, the field is still in its infancy. Future areas of focus include developing more robust 3D systems with color processing and artificial intelligence to handle biological variability and increase acceptability across multiple applications. Barriers to adoption include the need for specialized hardware and software as well as high system costs compared to benefits.
Image Processing in agro-based industries
- 1. IMAGE PROCESSING IN AGRO-BASED INDUSTRIES Sandeep Pawar (143350016)
- 3. Image processing in industries Source: Gunasekaran S, Vol. IV- Automation of food processing 3
- 4. 4 Source: Clarence W., Research Laboratory for fish processing automation
- 5. Image processing steps Image enhancement Image segmentation Feature extraction Template matching Pattern recognition 5
- 6. Image processing in food industries6 Physical properties of food- visual features Colour Most influential attribute Visual inspection : important part of quality control Texture Soft, hard, crispy, powdery, spongy Size and Shape Appearance, mouth feel Mass and volume
- 7. Product grading 7 Source: M.Omid et al, 2010, Journal of food engineering
- 8. Classification by texture analysis8 Source: A. Khoshroo et al, Classification of Pomegranate Fruit using Texture Analysis of MR Images (2009)
- 9. Image processing in packaging 9 Package inspection Label verification Seal inspection Wrinkle alignment Carton inspection Automatic glue placement
- 10. Image processing : two sides 10 Precision, objectivity, speed Saves tedious, inefficient manual inspection tasks Must be sufficiently flexible and robust to cope with biological flexibility Specialized hardware and software systems to cope up with ever increasing demands of speed and precision
- 11. Current scenario and Future scope11 Infancy stage Systems: successful under constrained conditions for specific applications Most of the systems 2D and monochromatic Needs 3D systems with colour processing More robust, humanlike (artificial intelligence) Developing generic image processing systems that can be used for multiple applications may increase acceptability.
- 12. Conclusion 12 Due to advances in electronics and computer technologies, vision systems can be installed in almost all food plants for an effective quality evaluation/control operation. One of the biggest barriers in applying machine vision to the food processing industry is the system cost. Though the system cost for image processing system has been significantly reduced the ratio of cost to benefit is still unacceptable in many potential applications.