Digital image processing

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Seminário apresentado em 11.2011

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  • These are the topics,
  • To enhance photo
  • To identification
  • Back in history…
  • But only with…
  • Now a days
  • Ok…now you know what is image processing…
  • So we can..
  • Image could also
  • One of the most important key role…
  • Knowing those basic concepts, tell you some steps
  • You can imagine the difficulty…. So that we have to plain our projects using some methodology
  • You don’t have an image processing project whitout a problem to solve
  • After defining you problem, you have to acquire the image



  • Or anothers kinds os sed imagnsors tha produces 2
  • After acquiring a image, probably its not ready for you start to seek your objetive. Than..
  • The thesholding process is one of the most aplied
  • After finishing the segmentation, you have to chose the best way to represent e describe your image
  • Then,
  • Now you have your objetcs described, naow yo have to recognize and interpret what it means
  • Finally, you have a group of recognized objects, but what they means
  • Digital image processing

    1. 1. Fundamentals steps for development Juan Guedes Pereira Digital Image Processing – Juan Guedes Pereira
    2. 2. Background  Why process image? Basic concepts  What you need to know? Fundamental steps  A methodology of project. Conclusion Digital Image Processing – Juan Guedes Pereira
    3. 3. Digital Image Processing – Juan Guedes Pereira
    4. 4. Interest in digital image processing method derives two principal application areas: Digital Image Processing – Juan Guedes Pereira Improvement of visual information for human interpretation Autonomous machine perception & industrial process
    5. 5. Improvement of visual information for human interpretation. Digital Image Processing – Juan Guedes Pereira
    6. 6. Autonomous machine perception. Digital Image Processing – Juan Guedes Pereira
    7. 7. One of the first applications was in improving digitized newspaper pictures sent by submarine cable between London and New York. Digital Image Processing – Juan Guedes Pereira
    8. 8. Advents of ... Digital Image Processing – Juan Guedes Pereira large-scale digital computers space program Brought into focus the potential of image processing concepts.
    9. 9. Image processing has been used to solve a bunch of problems. Digital Image Processing – Juan Guedes Pereira WEG.23 Industrial machine vision Processing of fingerprints Biomedical analysis Geographical mapping
    10. 10. Image processing has been used to solve a bunch of problems. Digital Image Processing – Juan Guedes Pereira
    11. 11. Digital Image Processing – Juan Guedes Pereira
    12. 12. The term monochrome image refers to a two- dimensional light intensity function f(x,y). Digital Image Processing – Juan Guedes Pereira x and y denote spatial coordinates Value of f is proportional to the brightness
    13. 13. A digital image can be considered a matrix whose row and column indices indentify a point in the image and the corresponding matrix element value indentifies the gray level at that point. Digital Image Processing – Juan Guedes Pereira
    14. 14. It’s very important for human comprehension a way to model an image color. The most applied it is the RGB model. Digital Image Processing – Juan Guedes Pereira
    15. 15. Images represented in the RGB color model consist of three component images – one for each primary color. Digital Image Processing – Juan Guedes Pereira
    16. 16. The transform theory. Digital Image Processing – Juan Guedes Pereira The Fourier transform decomposes functions into its constituent frequencies; Highlights some characteristics.
    17. 17. Digital Image Processing – Juan Guedes Pereira
    18. 18. Digital image processing includes a broad range of hardware, software and theory. Digital Image Processing – Juan Guedes Pereira
    19. 19. To improve you chance of success… Digital Image Processing – Juan Guedes Pereira ACQUISITION PREPROCESSING SEGMENTATION REPRESENTATION & DESCRIPTION RECOGNITION & INTERPRETATION KNOWLEDGE BASE POSTPROCESSING PROBLEM DOMAIN RESULT
    20. 20. The problem domain is defined as the subject to be process. This domain has the characteristics that will define the knowledge base. It contains, in somehow, the result that you are looking for. Digital Image Processing – Juan Guedes Pereira
    21. 21. Requires an image sensor and the capability to digitize the signal produced by the sensor. This sensor could be a monochrome or color TV camera. Digital Image Processing – Juan Guedes Pereira Produces an entire image of the problem domain in rate of some frames per seconds.
    22. 22. Requires an image sensor and the capability to digitize the signal produced by the sensor. The sensor could also be an x-ray camera. Digital Image Processing – Juan Guedes Pereira Produces by reflecting in some parts of an object a 2-D image.
    23. 23. The result has to be more suitable than the original one for a specific application. Digital Image Processing – Juan Guedes Pereira
    24. 24. There are two approaches for image enhancement, the special domain methods and the frequency domain methods. Digital Image Processing – Juan Guedes Pereira Special domain: Sobel filter frequency domain: low pass filter
    25. 25. The following steps deals with techniques for extracting information, we refer to this area as image analysis. Digital Image Processing – Juan Guedes Pereira
    26. 26. Segmentation is defined as partitions an input image into its constituent parts or object. In general, autonomous segmentation is one of the most difficult tasks in digital processing. Digital Image Processing – Juan Guedes Pereira
    27. 27. The best way to segment an image is to detect its discontinuities. Dots Lines Edges These three uses mathematical function as operator, such as gradient and laplacian functions Digital Image Processing – Juan Guedes Pereira
    28. 28. During the thresholding process, pixels in an image are marked as "object" pixels if their value is greater than some threshold value. The value histogram could be:  Gray level;  Color intensity;  Others values. The threshold value also could be  intensity average;  Median of a value. Digital Image Processing – Juan Guedes Pereira
    29. 29. A segmented region can be represented by boundary pixels or internal pixels. When shape is important, a boundary (external) representation is used. Digital Image Processing – Juan Guedes Pereira
    30. 30. A segmented region can be represented by boundary pixels or internal pixels. When color or texture is important, an internal representation is applied. Digital Image Processing – Juan Guedes Pereira
    31. 31. The next task is to describe the region based on the chosen representation. For internal representation :  Average;  Standard deviation;  Moment;  Entropy;  … Digital Image Processing – Juan Guedes Pereira
    32. 32. The next task is to describe the region based on the chosen representation. For boundary:  Diameter;  Area;  Perimeter  Major axis;  … Digital Image Processing – Juan Guedes Pereira
    33. 33. The last stage involves recognition and interpretation. Recognition is the process the assigns a label to an object based on the information provided by its descriptors. Digital Image Processing – Juan Guedes Pereira Major axis = 2,3 cm # of holes = 2 Hole #2 area = 25 mm2 Letter g
    34. 34. Different methods to recognize an image. Pattern matching Neural networks Digital Image Processing – Juan Guedes Pereira
    35. 35. Interpretation involves assigning meaning to an ensemble of recognizes object. Image analysis tasks can be as simple as… or as sophisticated as… Digital Image Processing – Juan Guedes Pereira reading bar coded tags identifying a person from their face
    36. 36. This interpretation requires a bunch of logical test and rules, which defines and, finally, gave meaning to the process. Methods for discovering relations between variables. Digital Image Processing – Juan Guedes Pereira If ( object == “n” and followed by object == “o” ) Then means = no.
    37. 37. Digital Image Processing – Juan Guedes Pereira
    38. 38. To process a image is becoming cheaper and easier; Anyone has access to a video camera; Software for image enhancement are as common as text editors; Digital Image Processing – Juan Guedes Pereira
    39. 39. Following that methodology of image processing increase your success probability; The most difficult task is to transfer our recognition and interpretation of an object to machine language. Digital Image Processing – Juan Guedes Pereira
    40. 40. How can we distinguish a scissor of a pliers? Digital Image Processing – Juan Guedes Pereira
    41. 41. Juan Guedes Pereira jgp@neo.ufsc.br www.facebook.com/juangp3 www.twitter.com/juangp3 www.neo.ufsc.br

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