INTRODUCTION DIGITAL IMAGE PROCESSING USING MATLAB

Image ProcessingMy- Ha Le, Ph.Dhalm@hcmute.edu.vnAugust 31, 2015Reading• Golzalez, Digital Image Processing (2nd Edition)• Golzalez, Digital Image Processing Using MATLAB• Richard Szeliski, Computer Vision: Algorithms and Applications, S[r]

ages/graphics. While it is possible to directly tap into the un-derlying application (e.g., an Internet browser) to performtext analysis in order to detect the presence of graphics, thisapproach would require that the system understands the pro-tocols of any possible application software a user may[r]

Hindawi Publishing CorporationEURASIP Journal on Advances in Signal ProcessingVolume 2009, Article ID 574627, 7 pagesdoi:10.1155/2009/574627Research ArticleRealization of Ternary Sigma-Delta Modulated ArithmeticProcessing ModulesAmin Z. Sadik and Peter J. O’SheaSchool of Engineer ing Systems, Queens[r]

Nowadays, new “digital” areas have brought in many new image and video applications and new technologies in different fields, such as biology, medicine, engineering, and entertainment. The images and videos are compressed, transmitted, captured, and stored in various digital for[r]

Nowadays, new “digital” areas have brought in many new image and video applications and new technologies in different fields, such as biology, medicine, engineering, and entertainment. The images and videos are compressed, transmitted, captured, and stored in various digital for[r]

ages/graphics. While it is possible to directly tap into the un-derlying application (e.g., an Internet browser) to performtext analysis in order to detect the presence of graphics, thisapproach would require that the system understands the pro-tocols of any possible application software a user may[r]

quality that we expect from professional trans-lators. The total cost is more than an order ofmagnitude lower than professional translation.1 IntroductionIn natural language processing research, translationsare most often used in statistical machine translation(SMT), where systems are trained[r]

1.2 ■ The Origins of Digital Image Processing3and, in addition, encompasses processes that extract attributes from images, upto and including the recognition of individual objects. As a simple illustrationto clarify these concepts, consider the area of automated analysis of text[r]

27. Otsu N: A Threshold Selection Method from Gray-Level His-tograms. IEEE Transactions on Systems, Man, and Cybernetics 1979,9:62-66.28. Gonzalez RC, Woods RE, Eddins SL: Digital Image Processing UsingMATLAB New Jersey: Pearson Prentice Hall; 2004. 29. Barron JL, Fleet DJ, Beau[r]

sent by inverting alternate code words before transmission. Consider a string of consecutive data bytes 40H, the codeword is –00+0+ which has weight +1. This is sent as the sequence –00+0+, +00–0–, –00+0+, +00–0– etc, which results in a mean signal level of zero. The receiver consequently reinverts[r]

sent by inverting alternate code words before transmission. Consider a string of consecutive data bytes 40H, the codeword is –00+0+ which has weight +1. This is sent as the sequence –00+0+, +00–0–, –00+0+, +00–0– etc, which results in a mean signal level of zero. The receiver consequently reinverts[r]

the five key features that are introduced in [7]. It is shownthat this method can achieve a satisfying performance atan SNR as low as 5 dB. This algorithm can recognize themodulation types of ASK2, ASK4, FSK2, FSK4, PSK2, andPSK2. As mentioned in [5], these features are only suitablefor these low ord[r]

novel image fusion algorithms which are able to provide visually more pleasing fusion results. LIP-based multiresolution imagefusion approaches are consequently formulated due to the generalized nature of the PLIP model. Computer simulations illustratethat the proposed image fusion alg[r]

removing dust particles or concealing larger corrupted areas, no published works are devoted to the restoration of soundtracksdegraded by substantial underexposure or overexposure. Digital restoration of optical soundtracks is an unexploited applicationfield and, besides, scientifically rich, b[r]

CHAPT ER 1Introduction to Microcontrollers IntroductionHistoryMicrocontrollers versus microprocessors1.1 Memory unit1.2 Central processing unit1.3 Buses1.4 Input-output unit1.5 Serial communication1.6 Timer unit1.7 Watchdog1.8 Analog to digital converter1.9 ProgramIntroductionCi[r]

TRANG 1 DIGITAL COMMUNICATION USING MATLAB®V.6 DR.[r]

3. FEEDBACK CONTROL FOR IMPROVEMENTOF CHARACTER RECOGNITION ININDUSTRIAL APPLICATIONS3.1. The problemAutomated reading of human-readable char acters, known asoptical character recognition (OCR) [ 20 ] is one of the mostdemanding tasks for computer vision systems since it has todeal with different pro[r]

mobile condition; it also permits recognition of banknotes,colors, and of objects through their barcode labels. Thefollowing two papers are concerned with more genericapproaches. In “Enabling seamless access to digital graphicalcontents for visually-impaired individuals via semantic-aware [r]