Xem mẫu
- om
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XỬ LÝ ẢNH
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an
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Võ Tuấn Kiệt
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Bộ môn Viễn thông (112B3)
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Đại học Bách Khoa TpHCM
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Email: kietleo@gmail.com
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- Chương 7: Chuyên đề xử lý ảnh
Phân lớp
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Khoảng cách tối thiểu
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Lân cận gần nhất (KNN)
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Xác suất Bayes
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- Nhận dạng
Pattern: is a arrange of descriptors
Pattern classes: a pattern class is a family of
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patterns that share some common properties
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Pattern recognition/classification: to assign
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patterns to their respective classes
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Intelligent
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Ability to separate relevant information
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Ability to learn from examples and to generalize
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knowledge so that it can be used in other
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situations
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Ability to draw conclusions from incomplete
information
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- Ví dụ
Mấy
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lớp?
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Mấy
ng
co
thông
an
số đo?
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- Lý thuyết quyết định
Decision-theoretic approaches to recognition are based on the use
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decision functions.
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Let x ( x , x ,..., x ) represent an n-dimensional pattern vector.
T
1 2 n
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For W pattern classes , ,..., , we want to find W decision
1 2 W
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functions d ( x ), d ( x ),..., d ( x )with the property that, if a pattern x
1 2 W
belongs to class , then
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d i (x ) d j (x )
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The decision boundary separating class
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and is given by
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d i (x ) d j (x ) or d i ( x ) d j (x ) 0
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- Phân lớp khoảng cách tối thiểu
Suppose that we define the prototype of each pattern
class to be the mean vector of the patterns of that class:
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1
m x
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j j
N j x w
where Nj is the number of pattern vectors from class wj j
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(j=1,2,…,W)
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Using the Euclidean distance to determine closeness
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reduces the problem to computing the distance
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measures
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D j (x) x m j
where T 1/ 2
|| a || (a a )
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- We assign x to class wi if Di(x) is the smallest
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distance.
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The smallest distance is equivalent
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to evaluating the
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T T
functions d ( x ) x m m m
j j j j
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2
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And assign x to class wi if di(x) yields the largest
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numerical value.
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The decision boundary between classes and for a
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minimum distance classifier is
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T 1 T
d ij ( x ) d i (x) d j (x) x (m i
m j) (m i
m j ) (m i
m j) 0
2
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- Giải thuật phân lớp khoảng cách tối thiểu
Each class is represented by its mean vector
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Training is done using the objects (pixels) of known class
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Mean of the feature vectors for the object within the class is
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calculated
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New objects are classified by finding the closest mean vector
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- Phân lớp lân cận gần nhất
Nearest neighbour classifier: A pattern in the
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test data is classified by calculating the
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distance to all the patterns in the training data.
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The class of the training pattern that gives the
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shortest distance determines the class of the
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test pattern.
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- Giải thuật KNN
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- Phân lớp xác suất Bayes
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co
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Naïve
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Zero frequency smoothing technique
(Laplace estimation)
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- Naïve Bayes using m-estimate
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- Phân bố xác suất
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- Hàm ngẫu nhiên 1 biến
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- Hàm ngẫu nhiên 2 biến
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Mean
Correlation
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Covariance
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- Phân bố Gaussian nhiều biến
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- om
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- Ôn tập
Nguyên lý cơ bản của nén ảnh?
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Các thông số đánh giá hiệu quả nén ảnh?
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Các kỹ thuật nén ảnh không tổn hao?
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co
Các bước cơ bản trong nén ảnh JPEG?
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Giải thuật phân lớp khoảng cách tối thiểu?
th
ng
Giải thuật phân lớp lân cận gần nhất?
o
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Giải thuật phân lớp xác suất Bayes?
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- Bài tập 7
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- Bài tập 8
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We are told that the fruit is Long, Sweet and
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Yellow. Is it a Banana? Is it an Orange? Or is it
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some Other Fruit?
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