PPT-Chapter 9 Morphological Image Processing

Dept Computer Science amp Engineering Hongtao Lu 11162016 Digital Image Processing 3 rd ed Preliminaries Erosion and Dilation Opening and Closing The HitorMiss Transformation Some Basic Morphological Algorithms. Dilation: Join Broken Segments Erosion and Dilation: Eliminating Irrelevant Details Closing Hit or Miss Operator Region Filling Connected Components Thinning Thickening: Thinning the complement Gray S 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”. ImagePandA. ). 7. . – . Morphological Image Processing. Christoph. . Lampert. / Chris . Wojtan. Based on . content from “Digital Image Processing” by Gonzalez and Woods. TexPoint fonts used in EMF. . 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. 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. 1. Image. Rich info. from visual data. Examples of images around us. natural photographic images; . . artistic and engineering drawings. scientific images (satellite, medical, etc.). “Motion pictures” => video. Chapter 9, Digital Image Processing, Gonzalez & Woods. Topics. Basic Morphological concepts. Four Morphological principles. Binary Morphological operations. Dilation & erosion. Hit-or-miss transformation. 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:. MORPHOLOGICAL PROCESSING #include " morph.h " void main ( int argc , char * argv []) { SE p; IMAGE im ; int k; if ( argc < 4) { printf (" BinDil <input> <Structuring element> <output>\n"); 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. 1 INTRODUCTIONImage processing is the frequently used technique in vast areas like medical image astronomical data analysisand so on The collection of images is increased to petabytes in last few Recognition Vol.7, No. 2 (2014), pp. 3 89 - 3 9 8 http://dx.d oi.org/10.14257/ijsip.2014.7. 2 . 3 6 ISSN: 2005 - 4254 IJSIP Copyright ⓒ 201 4 SERSC Extraction of Optic Cup in Retinal Fundus image