Project 4: Feature Detection

Due  Nov. 18
(points 200)

Grading: 50 points = ave from survey, 150 points using Binary Grading Fomula

    As a class you will collaborate to create a singe breast cancer feature detection system. Specifically, you will form sub-groups to detect specific features, the class will also elect one or more people to integrate all of these feature detection components into a single GUI applicaiton.

    Each subgroup will be given their own unique survey score and the rest of the points will be evaluated by the instructor via binary grading formula and will be the same for everyone participating in the project.

     

    Data Input

    JPG images from the USF database. You should be able to load each image and display it and then process it. The user of the system can then select a region of interest and request the system to process it. It is only in the ROI that features will be detect.

    Data Output

    You are to produce a single ascii data file representing each feature detected in a given ROI. The format of this data will be determined as part of your design process. You will need to specify the image file name, the ROI, number and type of each feature and details of feature. When calculating each feature, you will not only specify it but, also give an certainty metric on a scale of 0 to 100% indicating how true this feature is.

    Features

    Masses

    • shape
    • texture
    • size
    • lessions - stellate pattern (linear edges)
    • location?

    Microcalcifications

    • number of in ROI
    • distribution of in ROI
    • shape
    • size

     

     

    LABS

 

    CONSIDERATONS

     

     

     

     

    Implementation Details

    You will select a supervisor from your group to monitor progress on the project. Everyone must partcipate in all phases of this projects. Also, EVERYONE must be able to understand and reproduce the code created if necessary. If you do not individually complete the portion of the work allocated to you as stipulated by the supervisor, you will not be given credit on that phase of the project AND this work must then be redistributed by the supervisor to the rest of the class.

    Attendance throughout the class periods we will work on this project is CRITICAL and NECESSARY for credit on this project. ONLY absences excused by written doctor reports or other accepted excuses (see instructor) will be allowed and in this case a different individual project will be assigned to you.
     
     
     

Deliverables

  1. HTML paper on how you designed your MotionDetection Program.  Describe your approach and why you decided to take it. Note- you must address the problems discussed above as required above. Show results on the 2 images above. Discuss how you might improve your algorithm.
    Upload HTML w/images, etc. to one person's server account. Print out this HTML paper and write on top the URL of its location. YOU MUST create your own test sequence, in addition you must test using the sequences test1 and test2.
  2. Fully comment and test out program.
  3. Turn in diskette with all java code and compiled class files needed to run the program. IF YOU use additional classes not in standard Java, you need to have all of the files here...make a JAR file.
  4. Printout of code, fully commented, with YOUR NAME ON TOP, and INSTRUCTIONS ON HOW TO RUN THE CODE FROM YOUR DISKETTE.
  5. A one-page description of how code is structured and the state of how it works.
  6. A one-page description of each persons contribution to the project. If you have 3 people in your group this page should be formated by having 3 sections, each with a different person's name as the header. Under each section, describe that person's contributions to the design, code, and documentation development.
  7. Print outs of screen shots of program working showing the results of: image loading and display of image sequence before and after processing.

© Lynne Grewe