Image Processing Challenge

What is a common technique used for noise reduction in images?

• Gaussian Blur

• Sobel Operator

• Bilateral Filter

• Median Filter

Which algorithm is commonly used for edge detection in images?

• Canny edge detector

• Gaussian blur

• Laplacian edge detector

• Sobel edge detector

Name a method used for image segmentation.

• Watershed algorithm

• Gaussian blur

• K-means clustering

• Sobel operator

What is the purpose of feature extraction in image processing?

• To increase the file size of images without any purpose

• The purpose of feature extraction in image processing is to simplify images by extracting meaningful information for various tasks.

• To blur images for better clarity

• To complicate images by adding irrelevant information

Give an example of an image enhancement filter.

• Gaussian Blur

• Histogram Equalization

• Unsharp Mask

• Median Filter

How is object recognition achieved in images?

• Object recognition is accomplished by analyzing the audio data embedded in an image.

• Computer vision algorithms analyze features and patterns within an image using techniques like CNNs and deep learning models to achieve object recognition.

• Object recognition is achieved by counting the number of pixels in an image.

• Object recognition relies on the color composition of an image.

Explain the concept of Gaussian blur in image processing.

• Gaussian blur is a process of converting images to black and white

• Gaussian blur involves rotating the image pixels randomly

• Gaussian blur is achieved by increasing image contrast

• Gaussian blur in image processing is achieved by convolving the image with a Gaussian kernel to reduce noise and detail.

What role does thresholding play in image segmentation?

• Thresholding enhances the color saturation of an image for better segmentation results.

• Thresholding is a technique to blur the edges of objects in an image, making them harder to segment.

• Thresholding is used to add noise to an image, making segmentation more challenging.

• Thresholding helps in simplifying an image by reducing it to a binary image, making it easier to identify and extract objects of interest.

Describe the process of Canny edge detection.

• The process of Canny edge detection involves multiple steps such as applying Gaussian filter, calculating gradient magnitude, performing non-maximum suppression, double thresholding, and edge connectivity tracking.

• Canny edge detection is a single-step process with no intermediate stages

• The process of Canny edge detection involves counting pixels in the image

• Applying a median filter is the first step in Canny edge detection

How can histograms be used for image enhancement?

• By blurring the image

• By changing the image resolution

• By analyzing the distribution of pixel intensities and adjusting the histogram to improve contrast and quality.

• By rotating the image