PPT-Morphological Image Processing

By Dr Rajeev Srivastava What is Morphology Definition The filters can be described using set theoretic notation A set is a collection of pixels in the context of an image Morphological Operations. Image Processing. Md. . Rokanujjaman. Assistant Professor. Dept of Computer Science and Engineering. Rajshahi. University. What are Morphological Operations? . Morphological operations come from the word “morphing”. Books:. Chapter 11, Image Processing, Analysis, and Machine Vision, Sonka et al. Chapter 9, Digital Image Processing, Gonzalez & Woods. Topics. Basic Morphological concepts. Four Morphological principles. Color . Camera models, camera calibration. Advanced image pre-processing . Line detection. Corner detection. Maximally stable extremal regions. Mathematical Morphology. . binary. gray-scale. skeletonization. Color . Camera models, camera calibration. Advanced image pre-processing . Line detection. Corner detection. Maximally stable extremal regions. Mathematical Morphology. . binary. gray-scale. skeletonization. Pumice Depth Below . Water . as a Function of Time. Behnaz. Hosseini. Havre, MESH . and Pumice Experiments. P. umice deposits from 2012 . Kermadec. Islands submarine eruption north of New Zealand. Havre caldera samples collected by MESH team using remotely operated vehicle Jason. Alexander Fraser & Liane Guillou. {fraser,liane}@cis.uni-muenchen.de. CIS. , . Ludwig-Maximilians-Universität München. Computational . Morphology and Electronic Dictionaries. SoSe 2016. 2016-05-09. Embeddings. Ryan . Cotterell. , . Hinrich. . Schütze. , Jason Eisner. Morphology matters!. Morphologically rich is not the exception, it’s the rule!. Facts from WALS:. 85. % of all languages make use of affixation. Mohammadhossein . Behgam. Agenda. Need for parallelism. Challenges. Image processing algorithms. Data handling & Load Balancing. Communication cost & performance. What is the problem?. Image Processing applications can be very computationally demanding due to:. Divya Spandana . Marneni. Agenda. What is Big Data. Big Data and image processing. Why to analyze big images. Complexity involved in processing. Hadoop Image processing framework. Image Retrieval in big data. The relevant features for the examination task are enhanced. The irrelevant features for the examination task are removed/reduced. Here the input and output image are both digital image in color or gray scale.. References & Acknowledgement 1) Hwang, Y., G. Yu, H. Kang, & K. Nam. 2004. "Mental representation of Korean inflectional and derivational affixes." The Proceedings of conference of Korean Society for yuniberkeleyedu Huave a language isolate spoken in four villages of Oaxaca State Mexico has the unusual phenomenon of mobile affixes which surface as prefixes in some morphological contexts but as su Type II. Thin plate without any indication of the posteriorType III. Frail quadrilateral plate with small posterior clinoidType IV. Heavy square plate with well-developed posteriorType V. Thick elonga Dept. Computer Science & Engineering. Hongtao Lu. 11/16/2016. Digital Image Processing, 3. rd. ed.. Preliminaries. Erosion and Dilation. Opening and Closing. The Hit-or-Miss Transformation. Some Basic Morphological Algorithms.