Propelled Media and Design.

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Propelled Interactive media and Design Dr. Serhan Dagtas 12:15-1:30 pm Tue and Thu Acquaintance Presentation with the course Diagram, destinations, material, and so on. Prologue to sight and sound Course Layout Prologue to different media sorts; still pictures, video, sound, discourse, content, representation
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Propelled Multimedia and Graphics Dr. Serhan Dagtas 12:15-1:30 pm Tue & Thu

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Introduction to the course Outline, goals, material, and so on. Prologue to interactive media

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Course Outline Introduction to different media sorts; still pictures, feature, sound, discourse, content, illustrations Acquisition Compression procedures Analysis and indexing of sight and sound substance Multimedia recovery Storage Applications

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Course Objectives Understand the fundamentals of mixed media frameworks Store, process, and present mixed media information Image, sound, and feature indexing & recovery Work on examination ventures Computer representation and virtual reality

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Course Materials Textbooks Mutimedia Fundementals Vol. I, Multimedia Comm. Frameworks Handouts and web material

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Exams and ventures Exams Midterm Final Projects 3-5 assignments Group venture

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Policies Reading Read the parts Assignments may not be from address Attendance is normal

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Multimedia Media (plural of medium) Virtually any method for passing on data Mostly message, sound, pictures, feature Also music, crude information, realistic articles, and so forth. Sight and sound More than one media sort at the same time controlled

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Multimedia Information Systems Storage, Retrieval, Management and Analysis of data in any structure Images Video Audio Graphics, outlines, and so on. Content Data

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multiMEDIA what? Medium (media): A methods by which data is perceived… Or: A method for influencing or passing on something (data) “Multimedia” is a descriptive word !

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Multimedia Information Systems The intersection of a few innovations Digital sign handling Image preparing Computer design Digital Video innovation Visual intelligent dialects Advanced databases Operating frameworks Computer systems

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Some Enabling Factors Optical circle innovation extensive volumes protect quality Shift from simple to computerized preparing high determination picture high devotion sound

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Analog Video Digital Video loss of value in replicating can\'t be commented purchasers can\'t alter duplication without misfortune record, pursuit, altering quick arbitrary get to brilliant playback intuitive

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Enabling Factors (cont’d) Fiber optics innovation high transfer speed exactness speed Fast specific processors sound loads up feature loads up Better programming, continuous OS codec (programming just)

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Example application PTV & HMS

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Properties of Multimedia System Combination of Media Is any blend of media a sight and sound? Freedom Tightly coupled media are not considered sight and sound, e.g., a PC controlled feature recorder stores sound and feature yet they are firmly joined Computer bolstered coordination Communication frameworks

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Continuous versus Discrete media time-autonomous: content and representation Continuous media time-ward: sound and full movement feature

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Analog versus Advanced Analog Media spoke to utilizing genuine qualities Digital Media spoke to utilizing discrete qualities (whole numbers, quantized numbers, skimming point representations)

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Sampled media Sampled media Represented by discrete focuses (which may be genuine esteemed) Notice: Sampled does not suggest Digital

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Sampling - just taking voltage readings at settled focuses in time Uniform testing – examining at normal interims

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Digital Conversion Given voltage readings at focuses in time: Convert the readings to computerized Options for computerized representation: Integers Floating point values

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We’ll concentrate on... Computerized inspected media But… We need to comprehend the hidden persistent media...

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An Overview of Media Types We will take a gander at: content Image Sound Video

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Text Plain content: alphanumeric characters Most basic representation is ASCII Structured content Text records are organized (title, areas, …) There are numerous benchmarks and organizations: Word processor positions LaTex, PDF

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Text Compression is either lossy or lossless Text pressure is lossless Text pressure utilizes the way that a few characters and expressions seem more frequently than others

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Text pressure: Huffman coding Idea: appoint less bits to images that seem all the more regularly and more bits to images that are less frequently Example: Assume a document with 1000 Characters are e, t, x, and z Probability of event 0.8, 0.16, 0.02, and 0.02 In ordinary coding we require 2 bits for every image  2000 bits for the whole record Using Huffman: 1 for e, 01 for t, 001 for x, and 000 for z Total number of bits = 1000(1*.8+2*.16+3*.02+3*.02) = 1240

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Text pressure: run length coding Directly decrease the quantity of rehashing characters A keep running of any length is spoken to by: Sc, X, C Sc unique character X is the rehashed character C is the character tally

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Represent the expression by its token Input document Yes Phrase No add expression to lexicon and produce a token Did it show up some time recently? Content pressure: Lampel-Ziv-Welch (LZW) Idea: fabricate a word reference of expressions from the information record.

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LZW sample Assume a document with 10,000 characters If we utilize 8 bits for every character, we require 80,000 bits for the record Suppose the record has 2000 words or expressions out of which 500 are unmistakable We can utilize 9 bit tokens for every word or expression  aggregate number of bits is 18,000 bits

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Image human and PC Vision to see a picture and to comprehend its substance catching, examination, and removing components Computer vision/picture handling force levels determination separations and territories the part of shading Images versus Design pictures are caught, representation are made. pictures are successions of picture components, illustrations are a progression of summons. design may be changed over into (engineered) pictures

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REAL WORLD IMAGE Vision, Image Processing and Visualization Photography Image Processing Computer Vision Computer Graphics/Visualization SCENE DESCRIPTION

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What sort of images…? Face photographs: Mug shots Finger prints CAT-check information News photographs (general. Normally went with informative content) Surveillance (semi-particular domain,we could possibly comprehend what to search for). Feature portions Movies:general observation News telecast Sports

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Summary Multimedia data frameworks Enabling components Continuous versus discrete Analog versus computerized Text pi

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