Module 2.1: Boundary Extraction| Image Morphological Operation | Digital Image Processing #subscribe

Hello Students, Internal and external boundary extraction are fundamental operations in digital image morphology that help in understanding the shape and structure of objects within images. Internal Boundary Extraction Internal boundary extraction refers to the process of identifying the boundaries of an object within an image that separates it from its background. This is typically achieved by using morphological operations such as erosion. In this context, the inner boundary is calculated by subtracting an eroded version of the original image from the original itself, mathematically expressed as: Inner Boundary=Original Image−Eroded Image The eroded image is obtained by applying a structuring element to shrink the original image, which effectively removes outer pixels and highlights the internal shape of the object. This operation is particularly useful for analyzing the size, shape, and position of objects within an image. External Boundary Extraction External boundary extraction, on the other hand, focuses on identifying the outermost boundaries of an object or a specific region within an image. This is accomplished through dilation operations, where the dilated image is created by expanding the original image using a structuring element. The outer boundary can be defined as the difference between the dilated image and the original image, expressed as: Outer Boundary=Dilated Image−Original Image This method allows for the extraction of outlines of all objects present in the image. External boundaries are particularly valuable for tasks like image cropping and background removal, as they define the edges of regions or objects effectively. ​Together, both internal and external boundary extraction play essential roles in image processing, helping to formulate accurate representations of image features for further analysis. You may refer the following books to practice more numerical questions: 1. R.C.Gonzalez and R.E.Woods, “Digital Image Processing”, Prentice Hall, 3rd Edition,2011. 2. S. Sridhar , “Digital Image Processing”, Oxford University Press,2011 #DigitalImageProcessing #ImageProcessing #ComputerVision #MachineLearning #AIImageProcessing #ImageEnhancement #ImageSegmentation #ImageAnalysis #DataScience #DeepLearning #ImageRecognition #ImageFilters #OpenCV #ComputerGraphics #ImageProcessingTutorials #MorphologicalOperations #ImageMorphology #DigitalImageProcessing #digitalimageprocessing #btechexams #ImageProcessingNumericals #UniversityExams #BTechPreparation #MidTermExams #EndTermExams #EngineeringExams #NumericalProblems #ImageProcessingTutorials #BTechStudyGuide #DigitalSignalProcessing #ExamPreparation #EngineeringNumericals #IndiaBTechStudents #Erosion, #Dilation, #Opening, #Closing, #HitMissTransform, #TopHatTransform, #BlackHatTransform, #BoundaryExtraction, #NoiseReduction, #ShapeAnalysis, #ObjectDetection, #ImageSegmentation, #Thinning, #Thickening, #Skeletonization, #MathematicalMorphology, #ImageFiltering, #CVTutorials If you have any suggestion/feedback or if you want videos on any topic related to digital image processing , please do comments in my video or write email to me: [email protected]