Pertemuan2 IMAGE PROCESSING John Adler KKKomputasi dan Kecerdasan

Pertemuan-2: IMAGE PROCESSING John Adler KK-Komputasi dan Kecerdasan Buatan Teknik Komputer Universitas Komputer Indonesia. UNIKOM Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 1

Bahan kuliah pertemuan-2 • Permasalahan image processing : Capture, modelling, feature extraction, image segmentation • Sejarah Digital Image Processing (DIP) • Beberapa contoh • Key Stages in Digital Image Processing Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 2

Permasalahan image processing : Capture, MODELLING, FEATURE EXTRACTION, IMAGE SEGMENTATION Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 3

Permasalahan capture • Capture merupakan proses awal dari image processing untuk mendapatkan gambar • Proses capture membutuhkan alat-alat capture yang baik seperti kamera, scanner, light-pen dan lainnya, agar diperoleh gambar yang baik. • Gambar yang baik akan banyak membantu dalam proses selanjutnya. Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 4

Permasalahan Modeling Dalam modeling diperlukan analisa matematika yang cukup rumit, khususnya pemakaian kalkulus dan transformasi geometri. (inilah sebabnya di semua jurusan fakultas teknik, kuliah matematika menjadi sangat penting !!) Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 5

Permasalahan Feature Extraction • Setiap gambar mempunyai karakteristik tersendiri, sehingga fitur tidak dapat bersifat general tetapi sangat tergantung pada model dan obyek gambar yang digunakan. • Fitur dasar yang bisa diambil adalah warna, bentuk dan tekstur. Fitur yang lebih kompleks menggunakan segmentasi, clustering dan motion estimation • Pemakaian statistik dan probabilitas, pengolahan sinyal sampai pada machine learning diperlukan di sini TK 37404 Pengolahan Citra Tuesday, September 15, 6

Permasalahan Image Segmentation • Bagaimana memisahkan obyek gambar dengan backgroundnya • Bagaimana memisahkan setiap obyek gambar • Teknik clustering apa yang sesuai dengan model dan obyek gambar yang digunakan TK 37404 Pengolahan Citra Tuesday, September 15, 7

Contoh Postal Code Problem Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 8

SEJARAH DIGITAL IMAGE PROCESSING Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 9

Images taken from Gonzalez & Woods, Digital Image Processing (2002) History of Digital Image Processing • Early 1920 s: One of the first applications of digital imaging was in the newspaper industry – The Bartlane cable picture transmission service Early digital image – Images were transferred by submarine cable between London and New York – Pictures were coded for cable transfer and reconstructed at the receiving end on a telegraph printer Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 10

Images taken from Gonzalez & Woods, Digital Image Processing (2002) History of DIP (cont…) • Mid to late 1920 s: Improvements to the Bartlane system resulted in higher quality images – New reproduction processes based on photographic techniques – Increased number of tones in reproduced images Tuesday, September 15, 2020 Improved Early 15 tone digital image TK 37404 Pengolahan Citra 11

Images taken from Gonzalez & Woods, Digital Image Processing (2002) History of DIP (cont…) • 1960 s: Improvements in computing technology and the onset of the space race led to a surge of work in digital image processing – 1964: Computers used to improve the quality of images of the moon taken by the Ranger 7 probe – Such techniques were used in other space missions including the Apollo landings Tuesday, September 15, 2020 TK 37404 Pengolahan Citra A picture of the moon taken by the Ranger 7 12 probe minutes before

Images taken from Gonzalez & Woods, Digital Image Processing (2002) History of DIP (cont…) • 1970 s: Digital image processing begins to be used in medical applications – 1979: Sir Godfrey N. Hounsfield & Prof. Allan M. Cormack share the Nobel Prize in medicine for the invention of tomography, the technology behind Computerised Axial Tomography (CAT) scans Typical head slice CAT image Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 13

History of DIP (cont…) • 1980 s - Today: The use of digital image processing techniques has exploded and they are now used for all kinds of tasks in all kinds of areas – Image enhancement/restoration – Artistic effects – Medical visualisation – Industrial inspection – Law enforcement – Human computer interfaces Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 14

Beberapa Bidang Ilmu yang Berhubungan dengan Image v. Computer Graphics : Kreasi image v. Image processing : penyempurnaan atau manipulasi gambar- yang hasilnya gambar lain v. Computer vision : analisis isi image Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 15

Pengolahan Data Berdasarkan Input/Output INPUT OUTPUT IMAGE Image Processing DESKRIP Computer SI Graphics Tuesday, September 15, 2020 TK 37404 Pengolahan Citra DESKRIPSI Computer Vision Data Mining, dll 16

Dua Macam Aplikasi IP v. Meningkatkan informasi bergambar untuk interpretasi manusia v. Pemprosesan data image untuk menyimpan, mentransmisikan, dan merepresentasikan untuk persepsi mesin otonomi Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 17

Bidang yang Memanfaatkan IP Berdasarkan sumber dari image: v. Radiasi dari spektrum elektromagnetik v. Akustik v. Ultrasonik v. Elektronik (dalam bentuk sinar elektron yang digunakan dalam mikroskop elektron) v. Komputer (image sintetis yang digunakan untuk pemodelan dan visualisasi) Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 18

Persoalan di dalam IP • • Capture Modeling Feature Extraction Image Segmentation Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 19

Permasalahan Capture • Capture (menangkap gambar) merupakan proses awal dari image processing untuk mendapatkan gambar • Proses capture membutuhkan alat-alat capture yang baik seperti kamera, scanner, light-pen dan lainnya, agar diperoleh gambar yang baik. • Gambar yang baik akan banyak membantu dalam proses selanjutnya. Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 20

Alat-alat Capture Sesuai Frekuensinya Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 21

Hasil Capture : Gamma-Ray Imaging Nuclear Image : a. Bone scan b. PET (Positron Emission Tomography) image. Astronomical Observations c. Cygnus Loop Tuesday, September 15, 2020 Nuclear Reaction d. Radiasi Gamma TK 37404 Pengolahan Citra reaktor dari katup 22

Hasil Capture : X-Ray Imaging Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 23

Hasil Capture : Ultraviolet Imaging Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 24

Hasil Capture : Visible Imaging Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 25

Hasil Capture : Infrared Imaging Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 26

Hasil Capture : Imaging in Microwave Band Tuesday, September 15, 2020 v. Imaging radar : satu-satunya cara untuk menjelajahi daerah yang tidak dapat diakses dari permukaan bumi v. Radar image dari pegunungan di tenggara Tibet vperhatikan kejelasan detail gambar, tidak terhalang oleh awan atau kondisi atmosfer lain yang biasanya TKmengganggu 37404 Pengolahan Citra 27 gambar

Hasil Capture : Imaging in Microwave Band Aplikasi ilmu Geologi : eksplorasi mineral dan minyak menggunakan suara dalam spektrum suara rendah (ratusan Hz) Model seismik dari image cross-sectional Gambar panah menunjukkan perangkap (bright spots) hidrokarbon (minyak dan atau gas) Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 28

Hasil Capture : Ultrasound Imaging Peralatan medis : a. Bayi b. Melihat bayi dari sisi yang lain c. Thyroids d. Lapisan tulang menggambarkan lesion Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 29

Hasil Capture : Imaging in Radio Band Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 30

Menggenerate image oleh komputer • Fraktal : an iterative reproduction of basic pattern according to some mathematical rules (a) dan (b) • Pemodelan komputer 3 D (c) dan (d) Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 31

BEBERAPA CONTOH Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 32

Images taken from Gonzalez & Woods, Digital Image Processing (2002) Examples: Image Enhancement • One of the most common uses of DIP techniques: improve quality, remove noise etc Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 33

Examples: The Hubble Telescope • Launched in 1990 the Hubble telescope can take images of very distant objects • However, an incorrect mirror made many of Hubble’s images useless • Image processing techniques were used to fix this Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 34

Examples: Artistic Effects • Artistic effects are used to make images more visually appealing, to add special effects and to make composite images Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 35

Images taken from Gonzalez & Woods, Digital Image Processing (2002) Examples: Medicine • Take slice from MRI scan of canine heart, and find boundaries between types of tissue – Image with gray levels representing tissue density – Use a suitable filter to highlight edges Tuesday, September TK 37404 Pengolahan Citra Original MRI Image of a Dog Heart Edge Detection Image 15, 2020 36

Examples: GIS Images taken from Gonzalez & Woods, Digital Image Processing (2002) • Geographic Information Systems – Digital image processing techniques are used extensively to manipulate satellite imagery – Terrain classification – Meteorology Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 37

Images taken from Gonzalez & Woods, Digital Image Processing (2002) Examples: GIS (cont…) • Night-Time Lights of the World data set – Global inventory of human settlement – Not hard to imagine the kind of analysis that might be done using this data Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 38

Images taken from Gonzalez & Woods, Digital Image Processing (2002) Examples: Industrial Inspection • Human operators are expensive, slow and unreliable • Make machines do the job instead • Industrial vision systems are used in all kinds of industries • Can we trust them? Tuesday, September TK 37404 Pengolahan Citra 15, 2020 39

Examples: PCB Inspection • Printed Circuit Board (PCB) inspection – Machine inspection is used to determine that all components are present and that all solder joints are acceptable – Both conventional imaging and x-ray imaging are used Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 40

Images taken from Gonzalez & Woods, Digital Image Processing (2002) Examples: Law Enforcement • Image processing techniques are used extensively by law enforcers – Number plate recognition for speed cameras/automated toll systems – Fingerprint recognition – Enhancement of CCTV Tuesday, September TK 37404 Pengolahan Citra images 15, 2020 41

Examples: HCI • Try to make human computer interfaces more natural – Face recognition – Gesture recognition • Does anyone remember the user interface from “Minority Report”? • These tasks can be extremely difficult TK 37404 Pengolahan Citra Tuesday, September 15, 2020 42

Key Stages in Digital Image Processing Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 43

Key Stages in Digital Image Processing Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 44

nzalez & Woods, Digital Image Processing (2002) Key Stages in DIP: Image Aquisition Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 45

nzalez & Woods, Digital Image Processing (2002) Key Stages in DIP: Image Enhancement Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 46

nzalez & Woods, Digital Image Processing (2002) Key Stages in DIP: Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 47

nzalez & Woods, Digital Image Processing (2002) Key Stages in Digital Image Processing: Morphological Processing Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 48

nzalez & Woods, Digital Image Processing (2002) Key Stages in DIP: Segmentation Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 49

Images taken from Gonzalez & Woods, Digital Image Processing (2002) Key Stages in DIP: Object Recognition Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 50

nzalez & Woods, Digital Image Processing (2002) Key Stages in Digital Image Processing: Representation & Description Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 51

Key Stages in Digital Image Processing: Image Compression Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 52

Key Stages in Digital Image Processing: Colour Image Processing Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Tuesday, September 15, 2020 Colour Image Processing Compression TK 37404 Pengolahan Citra 53

Penutup Ada beberapa hal yang harus dikuasai sebelum menguasai materi di dalam image processing yaitu : matematika, aljabar, pengolahan sinyal, matriks dan transformasi linier, statistik, Struktur Data dan algoritma pemrograman. Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 54

Referensi slide • Brian Mac Namee, Digital Image Processing : Introduction, www. com. dit. ie/bmacnamee • Nana Ramadijanti, Image Processing : Day-1, Laboratorium Computer Vision, PENS-ITS, Surabaya • Achmad Basuki, Pengantar Pengolahan Citra, Laboratorium Computer Vision, PENS-ITS, Surabaya Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 55

Image Processing Mempelajari Apa? • http: //www. mathworks. com/products/image/d escription 1. html • http: //www. mathworks. com/products/image/d escription 2. html • http: //www. mathworks. com/products/image/d escription 3. html • http: //www. mathworks. com/products/image/d escription 4. html Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 56

Image Processing Mempelajari Apa? (Contd. ) • http: //www. mathworks. com/products/image/d escription 5. html • http: //www. mathworks. com/products/image/d escription 6. html • http: //www. mathworks. com/products/image/d escription 7. html Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 57

TERIMA KASIH Tuesday, September 15, 2020 TK 37404 Pengolahan Citra 58

INTRODUCTION �In electrical engineering and computer science image processing is any form of signal processing for which the input is an image, such as a photograph or video frame; the output of image processing may be either an image or, a set of characteristics or parameters related to the image. Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal-processing techniques to it. �Image processing usually refers to digital image processing, but optical and analog image processing also are possible. This article is about general techniques that apply to all of them. The acquisition of images (producing the input image in the first place) is referred to as imaging.

Definitions of Image Processing � • The general term "image processing" refers to a computer discipline wherein digital images are the main data object. This type of processing can be broken down into several sub-categories, including: compression, image enhancement, image filtering, image distortion, image display and coloring. � • Any activity that transforms an input image into an output image. Manipulation of an image to improve or change some quality of the image

This Process involves two aspects �Improving the visual appearance of images to a human viewer. �Preparing images for measurement of the features and structures present.

Why do we need it……? • Since the digital image is invisible it must prepare for viewing one or more output device. The digital image can be optimized for the application by enhancing or altering the appearance of the structures within it. • It might be possible to analyze the image in the computer and provide clues to the radiologist to help direct important/suspicious structure.

Acquiring Images • Since the digital image is invisible it must prepare for viewing one or more output device. The digital image can be optimized for the application by enhancing or altering the appearance of the structures within it. • It might be possible to analyze the image in the computer and provide clues to the radiologist to help direct important/suspicious structure.

High Resolution �The process of obtaining a high resolution (HR) image or a sequence of HR from a set of low resolution (LR) observation. �HR technique has applied to a variety of fields such as obtaining. �Improve still images. �High definition television. �High performance color liquid crystal display (LCD) screen. �Video surveillance. �Remote sensing and �Medical imaging.

Color Spaces • Conversion from RGB (The brightness of individual red, green and green signal at defined wavelength) to YIQ/YUV and to other color encoding schemes is straightforward and losses no information.

Image Sensors • Digital processing requires images to be obtained in the form of electrical signals. These signals can be digitized into sequence of numbers which can be processed by a computer.

Image Intensity Equalization using Histograms � Image intensity Equalization is the process of converting the given image into the desired manner using Histogram. In histogram equalization we are trying to maximize the image contrast by applying a gray level transform which tries to flatten the resulting histogram. The gray level transform is a scaled version of the original image's cumulative histogram. That is, the gray level transform T is given by T[i] = (G-1)c(i), where G is the number of gray levels and c(i) is the normalized cumulative histogram of the original image. When we want to specify a non-flat resulting histogram, we can use the following steps: � Specify the desired histogram g(z) � Obtain the transform which would equalize the specified histogram, Tg, and its inverse Tg-1 � Get the transform which would histogram equalize the original image, s=T[i] � Apply the inverse transform Tg-1 on the equalized image, that is z=Tg-1[s]

Input Image histogram Output Image corresponding histogram

Multiple Images: It may constitute a series of views of the same area using different wavelength of light and other signals. Examples includes the image processed by satellites those images may require processing. Hardware Requirement: A general purpose computer can be used for image processing; four key demands must be met • • high resolution image display Sufficient memory transfer bandwidth. Sufficient storage space Sufficient computing power.

Software Requirements: Adobe Photoshop, Corel draw, Serif photo plus Mat lab etc. CONCLUSION: Adobe The Image processing is used to get/acquire image in a desired manner by using some of the software’s shown above without affecting its original input image and their may not be loos of data during the conversion process.