Image Analysis Basics
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Questions and Answers

What is the first stage of the image analysis process?

  • Preprocessing (correct)
  • Feature Analysis
  • Transformation
  • Data Reduction

Which statement is true regarding 4-neighbors of a pixel?

  • They consist of four horizontal and vertical pixels. (correct)
  • They touch only the corners of the pixel.
  • They include diagonal neighbors.
  • They are irrelevant to image processing.

How are diagonal neighbors denoted in pixel coordinate relationships?

  • N4(p)
  • N2(p) (correct)
  • N8(p)
  • N4e(p)

Which distance measure condition ensures that the distance is always non-negative?

<p>D(p, q) &gt;= 0 (D)</p> Signup and view all the answers

What does data reduction in image analysis primarily involve?

<p>Transforming data into the frequency domain. (B)</p> Signup and view all the answers

What are 8-neighbors of a pixel?

<p>Both 4-neighbors and diagonal neighbors. (C)</p> Signup and view all the answers

Which of the following best describes the features analysis stage?

<p>Extracted features are evaluated for application use. (A)</p> Signup and view all the answers

Which neighbor configuration includes both horizontal and diagonal connections?

<p>8-neighbors (C)</p> Signup and view all the answers

What is the value of C(1,1) obtained from the convolution of matrices A and B?

<p>630 (B)</p> Signup and view all the answers

In the convolution of matrices A and B, what is the value of C(2,2)?

<p>600 (C)</p> Signup and view all the answers

Which MATLAB command is used to calculate the convolution of two matrices?

<p>conv2 (B)</p> Signup and view all the answers

What does the parameter 'same' signify in the MATLAB function conv2?

<p>Returns a result of the same size as A (C)</p> Signup and view all the answers

How many total elements were considered to calculate the probability P(20)?

<p>36 (B)</p> Signup and view all the answers

What value corresponds to P(255) in the histogram calculation?

<p>0.1111 (A)</p> Signup and view all the answers

What is the main advantage of using bilinear interpolation over nearest neighbor interpolation?

<p>It produces smoother images. (D)</p> Signup and view all the answers

In the context of convolution operations, what does matrix B represent?

<p>A kernel or filter for convolution (C)</p> Signup and view all the answers

What does image shrinking involve?

<p>Mapping groups of pixels to a single pixel. (B)</p> Signup and view all the answers

Which statistical representation is calculated from image data as per the histogram problem?

<p>Probability distribution of pixel intensities (B)</p> Signup and view all the answers

Which operation is fundamental to linear neighborhood-oriented image processing algorithms?

<p>Convolution and correlation. (C)</p> Signup and view all the answers

When performing a convolution operation, what is the initial step with the second array?

<p>Mirror it and align its center with the first array. (C)</p> Signup and view all the answers

What does the convolution operation calculate for each pixel?

<p>A weighted sum of the pixel values and their neighbors. (C)</p> Signup and view all the answers

If an image is shrunk by one-half, which of the following describes how it is achieved?

<p>Alternate rows and columns are deleted. (D)</p> Signup and view all the answers

In the example of convolution with arrays A and B, what is the role of the empty spots during calculation?

<p>They are calculated as zero. (C)</p> Signup and view all the answers

Which of the following is NOT a characteristic of bilinear interpolation?

<p>It can result in sharper images compared to nearest neighbor. (A)</p> Signup and view all the answers

What is the formula for Euclidean distance between points 𝑝 and 𝑞?

<p>$D(p, q) = (x - s)^2 + (y - t)^2$ (C)</p> Signup and view all the answers

Which of the following describes the city-block distance between two points?

<p>$D(p, q) = |x - s| + |y - t|$ (B)</p> Signup and view all the answers

What effect does nearest neighbor interpolation have on an image?

<p>It introduces a checkerboard effect. (C)</p> Signup and view all the answers

In bilinear interpolation, how is the pixel value determined between two adjacent pixels?

<p>By averaging the two pixel values. (C)</p> Signup and view all the answers

What is the maximum size of the zoomed image when performing bilinear interpolation on an M×N image?

<p>(2M-1) x (2N-1) (A)</p> Signup and view all the answers

What is one of the requirements for zooming an image?

<p>Creating new pixel locations. (A)</p> Signup and view all the answers

Which distance metric uses the formula $D(p, q) = max(|x - s|, |y - t|)$?

<p>Chessboard distance (A)</p> Signup and view all the answers

What is the main visual effect caused by using bilinear interpolation?

<p>Blurring (B)</p> Signup and view all the answers

What is the value produced by the convolution calculation (3 × (−1)) + (2 × 3) + (1 × 1)?

<p>4 (A)</p> Signup and view all the answers

In a 2D convolution, when is mirroring of the mask performed?

<p>Before shifting the mask across the image (A)</p> Signup and view all the answers

Which of the following forms the basis of a histogram of an image?

<p>The number of pixels at each color value (B)</p> Signup and view all the answers

What does the convolution operation primarily involve?

<p>Sliding a mask and multiplying corresponding values (A)</p> Signup and view all the answers

What is the final result stored in the array after the convolution operation described?

<p>{1, 5, 8, 8, 4, 1, −1} (A)</p> Signup and view all the answers

How is the floor operator indicated in mathematical notation?

<p>⌊x⌋ (A)</p> Signup and view all the answers

When shifting the 2D mask, what is the starting point of the process?

<p>The top left pixel of the image (B)</p> Signup and view all the answers

What does the variable nk represent in the context of image histograms?

<p>The number of pixels having the gray level r% (B)</p> Signup and view all the answers

What does the normalized histogram equation $P(r ext{ %}) = n ext{ %} / n$ represent?

<p>The estimate of the probability of occurrence of gray level $r ext{ %}$ (D)</p> Signup and view all the answers

In a low contrast image, the histogram is characterized by which of the following?

<p>Narrow width and centered towards the middle of the gray scale (C)</p> Signup and view all the answers

Which convolution case results in a length that is the size of the first vector plus the size of the second vector minus one?

<p>Full (B)</p> Signup and view all the answers

What does a histogram concentrated on the low side of the gray scale indicate about an image?

<p>It is a dark image (A)</p> Signup and view all the answers

What is the result of the convolution of vectors $u=[1, 0, 1]$ and $v=[2, 7]$ in the valid case?

<p>[2, 7] (D)</p> Signup and view all the answers

In image processing, what does a histogram skewed toward the high side of the gray scale indicate?

<p>The image has very high brightness (C)</p> Signup and view all the answers

In the same case of convolution with zero padding for $u=[1, 0, 1]$ and $v=[2, 7]$, what is the first convolution result?

<p>7 (D)</p> Signup and view all the answers

Which of the following statements is true regarding the sum of all components of a normalized histogram?

<p>It is equal to 1 (D)</p> Signup and view all the answers

Flashcards

Image Analysis

The process of manipulating image data to extract meaningful information for various computer vision tasks.

Preprocessing

A stage in image analysis where the focus is on preparing the image data for further processing by removing noise, artifacts, or unnecessary information.

Data Reduction

A step in image analysis where the goal is to summarize and condense the image data, either in the spatial domain (pixel values) or the frequency domain (transformations).

Features Analysis

The final stage of image analysis where the features extracted from the data reduction process are analyzed and evaluated for their use in the specific application.

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Neighbors of a Pixel

Pixels that share a common edge or corner within the image.

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Distance Measure

A measure that quantifies the distance between two pixels based on their coordinates, satisfying certain properties like non-negativity, symmetry, and the triangle inequality.

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Diagonal Neighbors

Neighbors that share a common vertex or corner (e.g., (x+1, y+1), (x-1, y-1)).

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8-Neighbors

Includes both 4-neighbors and diagonal neighbors. These are all the immediate neighbors of a pixel.

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Bilinear interpolation

A method of increasing image size by assigning pixel values based on a weighted average of neighboring pixels. It produces smoother results compared to nearest neighbor interpolation.

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Nearest neighbor Interpolation

A straightforward image resizing technique that assigns the same value to a larger pixel from a smaller one. Results in blocky and pixelated images.

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Image shrinking

Reducing the size of an image by deleting rows and columns, essentially selecting a subset of pixels.

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Convolution

A mathematical operation where an image is processed by calculating a weighted sum of pixel values and surrounding neighbors. It's used for various image processing tasks.

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Kernel

In convolution, the set of weights applied to the neighboring pixels to calculate the new pixel value.

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Convolution operation

The process of applying a kernel to every pixel in an image, essentially sliding the kernel over each pixel.

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Convolved image or output image

The result of applying a convolution operation to an image. It is derived from the weighted sum of the original pixel and neighbors.

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Correlation

The process of calculating a weighted sum of pixels and neighbors, similar to convolution, but uses different mathematical algorithms.

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Euclidean Distance

The Euclidean distance between points p (x, y) and q (s, t) is calculated using the square root of the sum of squared differences between their coordinates.

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City-Block Distance

The City-block distance, also known as Manhattan distance, between points p (x, y) and q (s, t) is calculated by adding the absolute differences in their x and y coordinates.

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Chessboard Distance

The Chessboard distance between points p (x, y) and q (s, t) is calculated by finding the maximum value between the absolute differences in their x and y coordinates.

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Zooming - Digital Image

Zooming in on a digital image involves increasing the number of pixels, aiming to magnify the image and reveal finer details.

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Over-sampling

Over-sampling is a technique used in zooming, where new pixel locations are created to enlarge the image.

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Padding

Padding refers to the process of adding extra pixels around the boundaries of a digital image to prepare it for interpolation, allowing for more accurate resizing.

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What is convolution?

Convolution is the process of applying a filter (mask) to an input signal (e.g., image). It involves sliding the filter over the input, multiplying corresponding elements, and summing the results to create a new output signal.

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What is a convolution operation?

The process of shifting a filter across an input signal, multiplying corresponding elements, and summing the results to produce an output value.

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How is a convolution operation performed?

A convolution operation involves calculating a partial result for each position of the filter over the input signal. Each partial result is stored in the resulting array (A * B).

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What is the floor operator?

The floor operator rounds a number down to the nearest integer less than or equal to the given number. It is denoted by ⌊x⌋.

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How does 2D convolution work?

In 2D convolution, the filter (usually 3x3) is mirrored and shifted across the input image (A). The shifting starts from the top-left pixel and proceeds row by row until the bottom-right pixel is processed.

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What is an image histogram?

The histogram of an image is a representation of the distribution of gray levels (pixel values) in the image. It shows how many pixels have each specific gray level value.

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How is the histogram function defined?

The histogram of an image is a discrete function that maps each gray level to the number of pixels with that level. The function is represented as 𝐻 (𝑟% ) = 𝑛%, where 𝑟% is the kth gray level and 𝑛% is the number of pixels with that gray level.

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What is the range of gray levels in an image?

The range of gray levels in an image is from 0 to L-1, where L is the total number of gray levels.

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Convolution of Matrices

The process of calculating a matrix by multiplying each element of one matrix with the corresponding element in another matrix and then summing the results for each corresponding position in the output matrix.

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Convolution Matrix

A matrix that represents a filter or kernel used to apply changes to an input matrix, often used in image processing.

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Valid Convolution

A specific method for calculating convolution where the output size is reduced, considering only the fully overlapping sections of the input and convolution matrices.

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Same Convolution

A specific method for calculating convolution where the output size matches the input size by padding the input matrix with zeros.

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conv2

A function in MATLAB used for performing convolution between two matrices.

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Image Histogram

A technique used to visualize the frequency distribution of pixel values in an image, representing the count of each pixel value.

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imhist

MATLAB function that calculates the histogram of an image based on its pixel values.

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Average Pixel Value

The sum of all pixel values within an image divided by the total number of pixels, providing a measure of overall brightness.

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Normalized Histogram

A normalized histogram is a representation of the probability distribution of grayscale values in an image. It's calculated by dividing the frequency of each grayscale level by the total number of pixels in the image.

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Histogram of a Dark Image

A dark image typically has more pixels with lower grayscale values, resulting in a histogram that is concentrated toward the left (darker) side of the gray scale.

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Histogram of a Bright Image

A bright image has more pixels with higher grayscale values, causing the histogram to be biased towards the right (brighter) side of the grayscale.

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Histogram of a Low Contrast Image

An image with low contrast has a narrow range of pixel intensities, resulting in a histogram that is compressed towards the middle of the grayscale.

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Histogram of a High Contrast Image

A high contrast image has a wide range of pixel intensities, leading to a histogram that covers a broad range of the grayscale.

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Convolution of Vectors

The convolution of two vectors is calculated by sliding one vector across the other, multiplying corresponding elements, and summing the results.

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Study Notes

Image Analysis

  • Image analysis manipulates image data to solve computer imaging problems.
  • The process has three main stages: preprocessing, data reduction, and feature analysis.

Preprocessing

  • This stage addresses obvious and simple requirements.
  • Examples include removing artifacts or unnecessary information (like borders from digitized film).

Data Reduction

  • Either reduces data in the spatial domain or converts it to the frequency domain.
  • Features can then be extracted for further analysis.

Feature Analysis

  • Examines and evaluates extracted features for their application value.

Basic Relationships Between Pixels

  • A pixel's neighbors are defined by their spatial relationships.
    • 4-neighbors are horizontal and vertical neighbors.
    • Diagonal neighbors are those diagonally adjacent.
    • 8-neighbors include both 4-neighbors and diagonal ones.

Distance Measures

  • Distance metrics quantify the separation between pixels.
    • Euclidean distance: √((x₁-x₂)² + (y₁-y₂)²).
    • City-block distance: |x₁-x₂| + |y₁-y₂|.
    • Chessboard distance: max(|x₁-x₂|, |y₁-y₂|).

Zooming and Shrinking

  • Zooming involves over-sampling and scaling.
    • Two steps are needed: new pixel location creation and gray level assignment.
      • Nearest neighbor and bilinear interpolation are common methods for assignment.

Convolution

  • A mathematical operation processing images by computing a weighted sum of pixel values and neighbors.
    • Used in image processing algorithms for various tasks.

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Description

This quiz covers the fundamental concepts of image analysis. It explores the three main stages of image processing: preprocessing, data reduction, and feature analysis. Additionally, it touches upon the relationships between pixels and various distance measures.

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