E251014

% Experiencia de Aprendizaje anterior
% Tarea: Manipular el brillo de una imagen
Ic=imread('flores.bmp');
[x,y,z]=size(Ic);
x1=x/2;
y1=y/2;
figure, imshow(Ic), title('Imagen original');
Ig=rgb2gray(Ic);
figure, imshow(Ig), title('Imagen escala de grises');
% + Brillo
for m=1:y1
for n=1:x1
Ig(n,m)=Ig(n,m)*1.3;
end
end
for m=y1+1:y
for n=1:x1
end
end
% + Oscuro
for m=1:y1
for n=x1+1:x
end
end
for m=y1+1:y
for n=x1+1:x
end
end
figure, imshow(Ig);
% NOTA:
% Implementar con programas y/o funciones propias del alumno.
% No usar funciones del matlab para procesamiento imagenes.
% En Practicas Calificadas y Examen final no se consideraràn las funciones
% del Matlab para procesamiento de imagenes.
%Funciones del Matlab "solo para referencia"
% Brillo
Ic=imread('flores.bmp');
Ig=rgb2gray(Ic);
% Funcion de matlab para mainuplar brillo y contraste: imadjust
help imadjust
% IMADJUST Adjust image intensity values or colormap.
% J = IMADJUST(I) maps the values in intensity image I to new values in J
% such that 1% of data is saturated at low and high intensities of I.
% This increases the contrast of the output image J.
%
% J = IMADJUST(I,[LOW_IN; HIGH_IN],[LOW_OUT; HIGH_OUT]) maps the values
% in intensity image I to new values in J such that values between LOW_IN
% and HIGH_IN map to values between LOW_OUT and HIGH_OUT. Values below
% LOW_IN and above HIGH_IN are clipped; that is, values below LOW_IN map
% to LOW_OUT, and those above HIGH_IN map to HIGH_OUT. You can use an
% empty matrix ([]) for [LOW_IN; HIGH_IN] or for [LOW_OUT; HIGH_OUT] to
% specify the default of [0 1]. If you omit the argument, [LOW_OUT;

% HIGH_OUT] defaults to [0 1].
%
% J = IMADJUST(I,[LOW_IN; HIGH_IN],[LOW_OUT; HIGH_OUT],GAMMA) maps the
% values of I to new values in J as described in the previous syntax.
% GAMMA specifies the shape of the curve describing the relationship
% between the values in I and J. If GAMMA is less than 1, the mapping is
% weighted toward higher (brighter) output values. If GAMMA is greater
% than 1, the mapping is weighted toward lower (darker) output values. If
% you omit the argument, GAMMA defaults to 1 (linear mapping).
J1 = imadjust(Ig);
figure, imshow(J1), title('Ajuste 1');
J1b = imadjust(J1);
figure, imshow(J1b), title('Ajuste 1b');
J2 = imadjust(Ig,[0.3 0.7],[]);
%Usando el Gamma
J3z=imadjust(Ig,[0 1],[0.2 1],0.2);
figure, imshow(J3z), title('Ajuste 3z');
J3=imadjust(Ig,[0 1],[0.2 1],1);
J3b=imadjust(Ig,[0 1],[0.2 1],2);
figure, imshow(J3b), title('Ajuste 3b');
J3c=imadjust(Ig,[0 1],[0.2 1],3);
figure, imshow(J3c), title('Ajuste 3c');
J4 = imadjust(Ig,[0.3 1],[0 1],1);
%Histograma
Ic = imread('flores.bmp');
Ig=rgb2gray(Ic);
% Funcion para mostrar el histograma: imhist
help imhist
% IMHIST Display histogram of image data.
% IMHIST(I) displays a histogram for the intensity image I whose number of
% bins are specified by the image type. If I is a grayscale image, IMHIST
% uses 256 bins as a default value. If I is a binary image, IMHIST uses
% only 2 bins.
%
% IMHIST(I,N) displays a histogram with N bins for the intensity image I
% above a grayscale colorbar of length N. If I is a binary image then N
% can only be 2.
%
% IMHIST(X,MAP) displays a histogram for the indexed image X. This
% histogram shows the distribution of pixel values above a colorbar of the
% colormap MAP. The colormap must be at least as long as the largest index
% in X. The histogram has one bin for each entry in the colormap.
%
% [COUNTS,X] = imhist(...) returns the histogram counts in COUNTS and the
% bin locations in X so that stem(X,COUNTS) shows the histogram. For
% indexed images, it returns the histogram counts for each colormap entry;
% the length of COUNTS is the same as the length of the colormap.

figure, imhist(Ig);
[c,x]=imhist(Ig);
figure, stem(x,c);
% Ecualizacion del histograma
help histeq
% HISTEQ Enhance contrast using histogram equalization.
% HISTEQ enhances the contrast of images by transforming the values in an
% intensity image, or the values in the colormap of an indexed image, so
% that the histogram of the output image approximately matches a specified
% histogram.
%
% J = HISTEQ(I,HGRAM) transforms the intensity image I so that the histogram
% of the output image J with length(HGRAM) bins approximately matches HGRAM.
% The vector HGRAM should contain integer counts for equally spaced bins
% with intensity values in the appropriate range: [0,1] for images of class
% double or single, [0,255] for images of class uint8, [0,65535] for images
% of class uint16, and [-32768, 32767] for images of class int16. HISTEQ
% automatically scales HGRAM so that sum(HGRAM) = NUMEL(I). The histogram of
% J will better match HGRAM when length(HGRAM) is much smaller than the
% number of discrete levels in I.
%
% J = HISTEQ(I,N) transforms the intensity image I, returning in J an
% intensity image with N discrete levels. A roughly equal number of pixels
% is mapped to each of the N levels in J, so that the histogram of J is
% approximately flat. (The histogram of J is flatter when N is much smaller
% than the number of discrete levels in I.) The default value for N is 64.
%
% [J,T] = HISTEQ(I) returns the gray scale transformation that maps gray
% levels in the intensity image I to gray levels in J.
he = histeq(Ig);
figure, imshow(Ig);
figure, imhist(Ig);
figure, imshow(he);
figure, imhist(he);
hea = histeq(Ig,5);
figure, imshow(hea);
figure, imhist(hea);
hea2 = histeq(Ig,10);
figure, imshow(hea2);
figure, imhist(hea2);
[he,t] = histeq(Ig);
figure, stem(t);
% Operaciones morfologicas I: Dilatacion y erosion de imaganes escala de grises
% OM = EE + I, EE = Elemento estructural
% Dilatación de escala de grises
% Dilatación de imagenes escala de grises
% I imagen
I=[ 0 0 0 0 0 0 0 0 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0;...
0 0 15 15 27 27 8 8 0 0 0;...
0 0 100 100 95 95 1 1 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0;...
64 64 128 128 255 255 255 128 128 64 64;...

64 64 128 128 255 255 255 128 128 64 64;...
0 0 0 0 0 255 255 255 0 0 0;...
0 0 0 0 0 255 255 255 0 0 0;...
0 0 0 0 0 128 128 128 0 0 0;...
0 0 0 0 0 128 128 128 0 0 0;...
0 0 0 0 0 64 64 64 0 0 0;...
0 0 0 0 0 64 64 64 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0]
figure, imshow(imresize(uint8(I),[480,480])), title('imagen original');
% Definicion del elemento estructural
% Funcion para definir el ee: strel
help strel
% STREL Create morphological structuring element.
% SE = STREL('arbitrary',NHOOD) creates a flat structuring element with
% the specified neigbhorhood. NHOOD is a matrix containing 1's and 0's;
% the location of the 1's defines the neighborhood for the morphological
% operation. The center (or origin) of NHOOD is its center element,
% given by FLOOR((SIZE(NHOOD) + 1)/2). You can also omit the 'arbitrary'
% string and just use STREL(NHOOD).
%
% SE = STREL('arbitrary',NHOOD,HEIGHT) creates a nonflat structuring
% element with the specified neighborhood. HEIGHT is a matrix the same
% size as NHOOD containing the height values associated with each nonzero
% element of NHOOD. HEIGHT must be real and finite-valued. You can also
% omit the 'arbitrary' string and just use STREL(NHOOD,HEIGHT).
%
% SE = STREL('ball',R,H,N) creates a nonflat "ball-shaped" (actually an
% ellipsoid) structuring element whose radius in the X-Y plane is R and
% whose height is H. R must be a nonnegative integer, and H must be a
% real scalar. N must be an even nonnegative integer. When N is greater
% than 0, the ball-shaped structuring element is approximated by a
% sequence of N nonflat line-shaped structuring elements. When N is 0, no
% approximation is used, and the structuring element members comprise all
% pixels whose centers are no greater than R away from the origin, and the
% corresponding height values are determined from the formula of the
% ellipsoid specified by R and H. If N is not specified, the default
% value is 8. Note: Morphological operations using ball approximations
% (N>0) run much faster than when N=0.
%
% SE = STREL('diamond',R) creates a flat diamond-shaped structuring
% element with the specified size, R. R is the distance from the
% structuring element origin to the points of the diamond. R must be a
% nonnegative integer scalar.
%
% SE = STREL('disk',R,N) creates a flat disk-shaped structuring element
% with the specified radius, R. R must be a nonnegative integer. N must
% be 0, 4, 6, or 8. When N is greater than 0, the disk-shaped structuring
% element is approximated by a sequence of N (or sometimes N+2)
% periodic-line structuring elements. When N is 0, no approximation is
% used, and the structuring element members comprise all pixels whose
% centers are no greater than R away from the origin. N can be omitted,
% in which case its default value is 4. Note: Morphological operations
% using disk approximations (N>0) run much faster than when N=0. Also,
% the structuring elements resulting from choosing N>0 are suitable for
% computing granulometries, which is not the case for N=0. Sometimes it
% is necessary for STREL to use two extra line structuring elements in the
% approximation, in which case the number of decomposed structuring
% elements used is N+2.
%
% SE = STREL('line',LEN,DEG) creates a flat linear structuring element
% with length LEN. DEG specifies the angle (in degrees) of the line as
% measured in a counterclockwise direction from the horizontal axis.
% LEN is approximately the distance between the centers of the

% structuring element members at opposite ends of the line.
%
% SE = STREL('octagon',R) creates a flat octagonal structuring element
% with the specified size, R. R is the distance from the structuring
% element origin to the sides of the octagon, as measured along the
% horizontal and vertical axes. R must be a nonnegative multiple of 3.
%
% SE = STREL('pair',OFFSET) creates a flat structuring element containing
% two members. One member is located at the origin; the second member's
% location is specified by the vector OFFSET. OFFSET must be a
% two-element vector of integers.
%
% SE = STREL('periodicline',P,V) creates a flat structuring element
% containing 2*P+1 members. V is a two-element vector containing
% integer-valued row and column offsets. One structuring element member
% is located at the origin. The other members are located at 1*V, -1*V,
% 2*V, -2*V, ..., P*V, -P*V.
%
% SE = STREL('rectangle',MN) creates a flat rectangle-shaped structuring
% element with the specified size. MN must be a two-element vector of
% nonnegative integers. The first element of MN is the number rows in the
% structuring element neighborhood; the second element is the number of
% columns.
%
% SE = STREL('square',W) creates a square structuring element whose
% width is W pixels. W must be a nonnegative integer scalar.
%
% Notes
% -----
% For all shapes except 'arbitrary', structuring elements are constructed
% using a family of techniques known collectively as "structuring element
% decomposition." The principle is that dilation by some large
% structuring elements can be computed faster by dilation with a sequence
% of smaller structuring elements. For example, dilation by an 11-by-11
% square structuring element can be accomplished by dilating first with a
% 1-by-11 structuring element and then with an 11-by-1 structuring
% element. This results in a theoretical performance improvement of a
% factor of 5.5, although in practice the actual performance improvement
% is somewhat less. Structuring element decompositions used for the
% 'disk' and 'ball' shapes are approximations; all other decompositions
% are exact.
% EE=cuadrado de lado 3 pixeles
ee=strel('square', 3)
ee1 = strel('square',11) % 11-by-11 square
ee2 = strel('line',10,45) % line, length 10, angle 45 degrees
ee3 = strel('disk',10) % disk, radius 10
ee4 = strel('ball',15,5) % ball, radius 15, height 5
% DILATACION
% Funcion Matlab para la dilatacion de imagenes: imdilate
help imdilate
% IMDILATE Dilate image.
% IM2 = IMDILATE(IM,SE) dilates the grayscale, binary, or packed binary
% image IM, returning the dilated image, IM2. SE is a structuring element
% object, or array of structuring element objects, returned by the STREL
% function.
%
% If IM is logical (binary), then the structuring element must be flat
% and IMDILATE performs binary dilation. Otherwise, it performs
% grayscale dilation. If SE is an array of structuring element
% objects, IMDILATE performs multiple dilations, using each
% structuring element in SE in succession.

%
% IM2 = IMDILATE(IM,NHOOD) dilates the image IM, where NHOOD is a
% matrix of 0s and 1s that specifies the structuring element
% neighborhood. This is equivalent to the syntax IIMDILATE(IM,
% STREL(NHOOD)). IMDILATE determines the center element of the
% neighborhood by FLOOR((SIZE(NHOOD) + 1)/2).
I1=imdilate(I,ee)
figure, imshow(imresize(uint8(I1),[480,480]));
I3=imread('igsg.bmp');
figure, imshow(I3), title('imagen original');
ee=strel('square', 30);
% Se aplica dilatacion
I4=imdilate(I3,ee);
figure, imshow(I4), title('imagen dilatada');
% Erosión de imagenes escala de grises
% I imagen
% I imagen
I=[ 0 0 0 0 0 0 0 0 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0;...
0 0 15 15 27 27 8 8 0 0 0;...
0 0 100 100 95 95 1 1 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0;...
64 64 128 128 255 255 255 128 128 64 64;...
64 64 128 128 255 255 255 128 128 64 64;...
0 0 0 0 0 255 255 255 0 0 0;...
0 0 0 0 0 255 255 255 0 0 0;...
0 0 0 0 0 128 128 128 0 0 0;...
0 0 0 0 0 128 128 128 0 0 0;...
0 0 0 0 0 64 64 64 0 0 0;...
0 0 0 0 0 64 64 64 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0;...
0 0 0 0 0 0 0 0 0 0 0]
figure, imshow(imresize(uint8(I),[480,480])), title('imagen original');
% EROSION
% Funcion Matlab para erosionar una imagen: imerode
help imerode
% IMERODE Erode image.
% IM2 = IMERODE(IM,SE) erodes the grayscale, binary, or packed binary image
% IM, returning the eroded image, IM2. SE is a structuring element
% object, or array of structuring element objects, returned by the
% STREL function.
%
% If IM is logical and the structuring element is flat, IMERODE
% performs binary erosion; otherwise it performs grayscale erosion. If
% SE is an array of structuring element objects, IMERODE performs
% multiple erosions of the input image, using each structuring element
% in succession.
%
% IM2 = IMERODE(IM,NHOOD) erodes the image IM, where NHOOD is an array
% of 0s and 1s that specifies the structuring element. This is
% equivalent to the syntax IMERODE(IM,STREL(NHOOD)). IMERODE uses this
% calculation to determine the center element, or origin, of the

% neighborhood: FLOOR((SIZE(NHOOD) + 1)/2).
% Se aplica erosión
I1=imerode(I,ee);
figure, imshow(imresize(uint8(I1),[480,480])), title('Imagen erosionada');
I3=imread('igsg.bmp');
figure, imshow(I3);
% Se aplica erosión
I4=imerode(I3,ee);
figure, imshow(I4), title('Imagen erosionada');
%=========================================================================
% Operaciones morfologicas II: Dilatacion y erosion de imagenes binarias
% Dilatacion de imagenes binarias:
% TAREA:
% 1. Implementar la dilatacion y erosion en "negro" de imagenes binarias
% 2. Explicar el algoritmo de las funciones dilatacion y erosion implementadas
% 3. Realizar el diagrama de flujo de las funciones implementadas
% Creando una imagen binaria
b=ones(64);
n=zeros(64);
I=[b n b n b n b n; n b n b n b n b];
%I=imread('patron.bmp');
figure, imshow(I), title('Imagen original');
m=strel('square',20);
I1=imdilate(I,m);
figure, imshow(I1), title('Imagen dilatada');
% Erosión de imagenes binarias:
% I=imread('patron.bmp');
I2=[b n b n b n b n; n b n b n b n b];
figure, imshow(I2), title('Imagen original');
m=strel('square',20);
I2=imerode(I2,m);
figure, imshow(I2), title('Imagen erosionada');
% TAREA.
% 1. Explicar el algoritmo de las funciones dilatacion y erosion de la EA
% 2. Realizar el diagrama de flujo de las funciones
% Ejemplos: Con funciones
I=imread('joyas.bmp');
figure, imshow(I), title('Imagen original');
J=rgb2gray(I);
figure, imshow(J), title('Imagen escala de grises');
imwrite(J,'joyasG.bmp');
% K=im2bw(J,0.2);
% K=im2bw(J,0.5);
K=im2bw(J,0.7);
figure, imshow(K), title('Imagen binaria');
imwrite(K,'joyasB.bmp');
% Dilatacion escala de grises
dg=dilatacion(J);
figure, imshow(dg), title('Dilatacion escala de grises');

dg2=dilatacion(K);
figure, imshow(K), title('Dilatacion binaria');
% Erosion escala de grises
dg=erosion(J);
figure, imshow(dg), title('Erosion escala de grises')
dg2=erosion(K);
figure, imshow(K), title('Erosion binaria')
% Apertura = Erosion + Dilatacion
% Recupera elementos mayores redondeando sus contornos
% La funcion Matlab para la apertura de imagenes: imopen
help imopen
% IMOPEN Morphologically open image.
% IM2 = IMOPEN(IM,SE) performs morphological opening on the grayscale
% or binary image IM with the structuring element SE. SE must be a
% single structuring element object, as opposed to an array of
% objects.
%
% IM2 = IMOPEN(IM,NHOOD) performs opening with the structuring element
% STREL(NHOOD), where NHOOD is an array of 0s and 1s that specifies the
% structuring element neighborhood.
%
% The morphological open operation is an erosion followed by a dilation,
% using the same structuring element for both operations.
Ic=imread('iopen.jpg');
Ig=rgb2gray(Ic);
Ib=im2bw(Ig,0.7);
figure, imshow(Ib), title('Imagen binaria original');
ee=strel('square',5);
Io=imopen(Ib,ee);
figure, imshow(Io), title('Imagen binaria abierta');
Io1=imopen(Ib,ee);
figure, imshow(Io1), title('Imagen binaria abierta 2');
Io2=imopen(Ib,ee);
figure, imshow(Io2), title('Imagen binaria abierta 3');
% se = strel('disk',5);
% TAREA:
% Realizar con todos los tipos de elementos estructurales
% Clausura = Erosion + Dilatacion
% Permite unir elementos
% La funcion Matlab para la apertura de imagenes: imopen
help imclose
% IMCLOSE Morphologically close image.
% IM2 = IMCLOSE(IM,SE) performs morphological closing on the
% grayscale or binary image IM with the structuring element SE. SE
% must be a single structuring element object, as opposed to an array
% of objects.

%
% IMCLOSE(IM,NHOOD) performs closing with the structuring element
% STREL(NHOOD), where NHOOD is an array of 0s and 1s that specifies the
% structuring element neighborhood.
%
% The morphological close operation is a dilation followed by an erosion,
% using the same structuring element for both operations.
figure, imshow(Ib), title('Imagen binaria original');
Io=imclose(Ib,ee);
figure, imshow(Io), title('Imagen binaria cerrada');
Io1=imclose(Ib,ee);
figure, imshow(Io1), title('Imagen binaria cerrada 2');
Io2=imclose(Ib,ee);
figure, imshow(Io2), title('Imagen binaria cerrada 3');
% Extracción de Bordes
% B = I- erosion(I)
% Rellenado de regiones
% 1. Extraer borde
% 2. Se toma un punto (0) dentro del borde
% 3. Erosionar el punto 0. i=1
% 4. Resultado punto nuevo. i=i+1
% 5. Erosionar punto nuevo
% 6. i=npii? No: Paso 4
% 7. Si: Sumar 1. + 5.
%

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