IT-523: Digital Image Processing (3-0-0-3)

Aditya TatuFB-1, Room no. 1206, Ext: 540

Practical matters

Lectures: Monday & Thursday 11:00-12:00, Wednesday08:30-09:30 - CEP 202

Attendance in lectures not mandatory, but I will assume thatyou are aware of topics covered and announcements made inclass.

Grades: Two In-sems (∼ 30%), End-sem (∼ 30%), Regularlab assignments (∼ 20%), Project and Lab exam(∼ 20%).

IT-523 DIP: Lecture 1 2/10

Practical matters

Lectures: Monday & Thursday 11:00-12:00, Wednesday08:30-09:30 - CEP 202

Attendance in lectures not mandatory, but I will assume thatyou are aware of topics covered and announcements made inclass.

Grades: Two In-sems (∼ 30%), End-sem (∼ 30%), Regularlab assignments (∼ 20%), Project and Lab exam(∼ 20%).

IT-523 DIP: Lecture 1 2/10

Practical matters

Lectures: Monday & Thursday 11:00-12:00, Wednesday08:30-09:30 - CEP 202

Attendance in lectures not mandatory, but I will assume thatyou are aware of topics covered and announcements made inclass.

Grades: Two In-sems (∼ 30%), End-sem (∼ 30%), Regularlab assignments (∼ 20%), Project and Lab exam(∼ 20%).

IT-523 DIP: Lecture 1 2/10

Project

Work on any small problem of your choice, for eg. facedetection/recognition, signature verification, identifying carlogos, image stitching, text recognition, identifying the book,gesture recognition, face warping, etc.

Understand and/or implement a good paper.

It is important for you to understand the issues involved, notthat important to show that your code is working, thereforeDo not copy, especially without giving due credit.

IT-523 DIP: Lecture 1 3/10

Project

Work on any small problem of your choice, for eg. facedetection/recognition, signature verification, identifying carlogos, image stitching, text recognition, identifying the book,gesture recognition, face warping, etc.

Understand and/or implement a good paper.

It is important for you to understand the issues involved, notthat important to show that your code is working, thereforeDo not copy, especially without giving due credit.

IT-523 DIP: Lecture 1 3/10

Project

Work on any small problem of your choice, for eg. facedetection/recognition, signature verification, identifying carlogos, image stitching, text recognition, identifying the book,gesture recognition, face warping, etc.

Understand and/or implement a good paper.

It is important for you to understand the issues involved, notthat important to show that your code is working, thereforeDo not copy, especially without giving due credit.

IT-523 DIP: Lecture 1 3/10

Practical matters

Textbook & References:

� Digital Image Processing, Gonzalez & Woods, 2nd or 3rd ed.(Textbook)

� Fundamentals of Digital Image Processing, Anil Jain� Digital Image Processing, William Pratt� Digital Image Processing, Kenneth R. Castleman

Prerequisites: Signals & Systems, Linear Algebra, MATLAB.

IT-523 DIP: Lecture 1 4/10

Practical matters

Textbook & References:

� Digital Image Processing, Gonzalez & Woods, 2nd or 3rd ed.(Textbook)

� Fundamentals of Digital Image Processing, Anil Jain� Digital Image Processing, William Pratt� Digital Image Processing, Kenneth R. Castleman

Prerequisites: Signals & Systems, Linear Algebra, MATLAB.

IT-523 DIP: Lecture 1 4/10

Practical matters

Textbook & References:

� Digital Image Processing, Gonzalez & Woods, 2nd or 3rd ed.(Textbook)

� Fundamentals of Digital Image Processing, Anil Jain� Digital Image Processing, William Pratt� Digital Image Processing, Kenneth R. Castleman

Prerequisites: Signals & Systems, Linear Algebra, MATLAB.

IT-523 DIP: Lecture 1 4/10

Practical matters

Textbook & References:

� Digital Image Processing, Gonzalez & Woods, 2nd or 3rd ed.(Textbook)

� Fundamentals of Digital Image Processing, Anil Jain� Digital Image Processing, William Pratt� Digital Image Processing, Kenneth R. Castleman

Prerequisites: Signals & Systems, Linear Algebra, MATLAB.

IT-523 DIP: Lecture 1 4/10

Practical matters

Textbook & References:

� Digital Image Processing, Gonzalez & Woods, 2nd or 3rd ed.(Textbook)

� Fundamentals of Digital Image Processing, Anil Jain� Digital Image Processing, William Pratt� Digital Image Processing, Kenneth R. Castleman

Prerequisites: Signals & Systems, Linear Algebra, MATLAB.

IT-523 DIP: Lecture 1 4/10

Practical matters

Textbook & References:

� Digital Image Processing, Gonzalez & Woods, 2nd or 3rd ed.(Textbook)

� Fundamentals of Digital Image Processing, Anil Jain� Digital Image Processing, William Pratt� Digital Image Processing, Kenneth R. Castleman

Prerequisites: Signals & Systems, Linear Algebra, MATLAB.

IT-523 DIP: Lecture 1 4/10

Lab assignments

There will be regular lab assignments, usually once a week.

Register on courses.daiict.ac.in for course material andassignment submission.

Lab reports to be written strictly using LATEX; one submissionper group of at most 3 students. Do not change groups.

You may write required codes in C++ using standard imageprocessing libraries like OpenCV and CImg.

Use the Window shopping week to learnMATLAB/OpenCV/CImg.

IT-523 DIP: Lecture 1 5/10

Lab assignments

There will be regular lab assignments, usually once a week.

Register on courses.daiict.ac.in for course material andassignment submission.

Lab reports to be written strictly using LATEX; one submissionper group of at most 3 students. Do not change groups.

You may write required codes in C++ using standard imageprocessing libraries like OpenCV and CImg.

Use the Window shopping week to learnMATLAB/OpenCV/CImg.

IT-523 DIP: Lecture 1 5/10

Lab assignments

There will be regular lab assignments, usually once a week.

Register on courses.daiict.ac.in for course material andassignment submission.

Lab reports to be written strictly using LATEX; one submissionper group of at most 3 students. Do not change groups.

You may write required codes in C++ using standard imageprocessing libraries like OpenCV and CImg.

Use the Window shopping week to learnMATLAB/OpenCV/CImg.

IT-523 DIP: Lecture 1 5/10

Lab assignments

There will be regular lab assignments, usually once a week.

Register on courses.daiict.ac.in for course material andassignment submission.

Lab reports to be written strictly using LATEX; one submissionper group of at most 3 students. Do not change groups.

You may write required codes in C++ using standard imageprocessing libraries like OpenCV and CImg.

Use the Window shopping week to learnMATLAB/OpenCV/CImg.

IT-523 DIP: Lecture 1 5/10

Lab assignments

There will be regular lab assignments, usually once a week.

Register on courses.daiict.ac.in for course material andassignment submission.

Lab reports to be written strictly using LATEX; one submissionper group of at most 3 students. Do not change groups.

You may write required codes in C++ using standard imageprocessing libraries like OpenCV and CImg.

Use the Window shopping week to learnMATLAB/OpenCV/CImg.

IT-523 DIP: Lecture 1 5/10

Related courses

Computer Vision (Autumn, Prof. M.V.Joshi)

Topics in Image Analysis (Autumn, Aditya Tatu)

Pattern Recognition & Machine Learning (Winter, Prof.Suman Mitra)

IT-523 DIP: Lecture 1 6/10

Related courses

Computer Vision (Autumn, Prof. M.V.Joshi)

Topics in Image Analysis (Autumn, Aditya Tatu)

Pattern Recognition & Machine Learning (Winter, Prof.Suman Mitra)

IT-523 DIP: Lecture 1 6/10

Related courses

Computer Vision (Autumn, Prof. M.V.Joshi)

Topics in Image Analysis (Autumn, Aditya Tatu)

Pattern Recognition & Machine Learning (Winter, Prof.Suman Mitra)

IT-523 DIP: Lecture 1 6/10

Digital Image Processing

What is Digital Image Processing (DIP) ?

Definition: Processing multi-dimensional (usually two) signals(digital).

Applications:

� Image processing softwares: Photoshop, Irfanview etc.� Plays a major role in machine automation, for eg: identifying

parts and assembling them, detecting defective parts,identifying obstacles for robot navigation, license platerecognition, face recognition etc.

� Medical Image analysis: Identifying fractures in an X-rayimage, identifying tumour cells in different medical imagingmodalities, image guided surgery.

� Object recognition & tracking, Image and Video compression,etc.

� Remote sensing & GIS.

IT-523 DIP: Lecture 1 7/10

Digital Image Processing

What is Digital Image Processing (DIP) ?

Definition: Processing multi-dimensional (usually two) signals(digital).

Applications:

� Image processing softwares: Photoshop, Irfanview etc.� Plays a major role in machine automation, for eg: identifying

parts and assembling them, detecting defective parts,identifying obstacles for robot navigation, license platerecognition, face recognition etc.

� Medical Image analysis: Identifying fractures in an X-rayimage, identifying tumour cells in different medical imagingmodalities, image guided surgery.

� Object recognition & tracking, Image and Video compression,etc.

� Remote sensing & GIS.

IT-523 DIP: Lecture 1 7/10

Digital Image Processing

What is Digital Image Processing (DIP) ?

Definition: Processing multi-dimensional (usually two) signals(digital).

Applications:

� Image processing softwares: Photoshop, Irfanview etc.� Plays a major role in machine automation, for eg: identifying

parts and assembling them, detecting defective parts,identifying obstacles for robot navigation, license platerecognition, face recognition etc.

� Medical Image analysis: Identifying fractures in an X-rayimage, identifying tumour cells in different medical imagingmodalities, image guided surgery.

� Object recognition & tracking, Image and Video compression,etc.

� Remote sensing & GIS.

IT-523 DIP: Lecture 1 7/10

Digital Image Processing

What is Digital Image Processing (DIP) ?

Definition: Processing multi-dimensional (usually two) signals(digital).

Applications:

� Image processing softwares: Photoshop, Irfanview etc.� Plays a major role in machine automation, for eg: identifying

parts and assembling them, detecting defective parts,identifying obstacles for robot navigation, license platerecognition, face recognition etc.

� Medical Image analysis: Identifying fractures in an X-rayimage, identifying tumour cells in different medical imagingmodalities, image guided surgery.

� Object recognition & tracking, Image and Video compression,etc.

� Remote sensing & GIS.

IT-523 DIP: Lecture 1 7/10

Digital Image Processing

What is Digital Image Processing (DIP) ?

Definition: Processing multi-dimensional (usually two) signals(digital).

Applications:

� Image processing softwares: Photoshop, Irfanview etc.� Plays a major role in machine automation, for eg: identifying

parts and assembling them, detecting defective parts,identifying obstacles for robot navigation, license platerecognition, face recognition etc.

� Medical Image analysis: Identifying fractures in an X-rayimage, identifying tumour cells in different medical imagingmodalities, image guided surgery.

� Object recognition & tracking, Image and Video compression,etc.

� Remote sensing & GIS.

IT-523 DIP: Lecture 1 7/10

Digital Image Processing

What is Digital Image Processing (DIP) ?

Definition: Processing multi-dimensional (usually two) signals(digital).

Applications:

� Image processing softwares: Photoshop, Irfanview etc.� Plays a major role in machine automation, for eg: identifying

parts and assembling them, detecting defective parts,identifying obstacles for robot navigation, license platerecognition, face recognition etc.

� Medical Image analysis: Identifying fractures in an X-rayimage, identifying tumour cells in different medical imagingmodalities, image guided surgery.

� Object recognition & tracking, Image and Video compression,etc.

� Remote sensing & GIS.

IT-523 DIP: Lecture 1 7/10

Digital Image Processing

What is Digital Image Processing (DIP) ?

Definition: Processing multi-dimensional (usually two) signals(digital).

Applications:

� Image processing softwares: Photoshop, Irfanview etc.� Plays a major role in machine automation, for eg: identifying

parts and assembling them, detecting defective parts,identifying obstacles for robot navigation, license platerecognition, face recognition etc.

� Medical Image analysis: Identifying fractures in an X-rayimage, identifying tumour cells in different medical imagingmodalities, image guided surgery.

� Object recognition & tracking, Image and Video compression,etc.

� Remote sensing & GIS.

IT-523 DIP: Lecture 1 7/10

Digital Image Processing

What is Digital Image Processing (DIP) ?

Definition: Processing multi-dimensional (usually two) signals(digital).

Applications:

� Image processing softwares: Photoshop, Irfanview etc.� Plays a major role in machine automation, for eg: identifying

parts and assembling them, detecting defective parts,identifying obstacles for robot navigation, license platerecognition, face recognition etc.

� Medical Image analysis: Identifying fractures in an X-rayimage, identifying tumour cells in different medical imagingmodalities, image guided surgery.

� Object recognition & tracking, Image and Video compression,etc.

� Remote sensing & GIS.

IT-523 DIP: Lecture 1 7/10

Course contents

Image acquisition - Image formation model, Sampling,Intensity quantization.

Terminology related to an image: Pixel, Neighborhood,connectivity etc.

Processing:� Image Enhancement (Pre-processing): Goal is to make the

image more conducive to further processing or viewing.Noise removal, Contrast enhancement, adjust brightness,sharpening, re-sample etc.

� Image restoration: Undoing a degradation process of theimage. We will study Linear Shift Invariant (LSI) degradationsystems only, for eg: Camera impulse response, Motion bluretc.

� Compression: A standard gray-scale image, let’s say1024 × 1024 pixels, without compression will require about 1MB memory! We will study some lossy and losslesscompression schemes including the well-known JPEG scheme.

IT-523 DIP: Lecture 1 8/10

Course contents

Image acquisition - Image formation model, Sampling,Intensity quantization.

Terminology related to an image: Pixel, Neighborhood,connectivity etc.

Processing:� Image Enhancement (Pre-processing): Goal is to make the

image more conducive to further processing or viewing.Noise removal, Contrast enhancement, adjust brightness,sharpening, re-sample etc.

� Image restoration: Undoing a degradation process of theimage. We will study Linear Shift Invariant (LSI) degradationsystems only, for eg: Camera impulse response, Motion bluretc.

� Compression: A standard gray-scale image, let’s say1024 × 1024 pixels, without compression will require about 1MB memory! We will study some lossy and losslesscompression schemes including the well-known JPEG scheme.

IT-523 DIP: Lecture 1 8/10

Course contents

Image acquisition - Image formation model, Sampling,Intensity quantization.

Terminology related to an image: Pixel, Neighborhood,connectivity etc.

Processing:� Image Enhancement (Pre-processing): Goal is to make the

image more conducive to further processing or viewing.Noise removal, Contrast enhancement, adjust brightness,sharpening, re-sample etc.

� Image restoration: Undoing a degradation process of theimage. We will study Linear Shift Invariant (LSI) degradationsystems only, for eg: Camera impulse response, Motion bluretc.

� Compression: A standard gray-scale image, let’s say1024 × 1024 pixels, without compression will require about 1MB memory! We will study some lossy and losslesscompression schemes including the well-known JPEG scheme.

IT-523 DIP: Lecture 1 8/10

Course contents

Image acquisition - Image formation model, Sampling,Intensity quantization.

Terminology related to an image: Pixel, Neighborhood,connectivity etc.

Processing:� Image Enhancement (Pre-processing): Goal is to make the

image more conducive to further processing or viewing.Noise removal, Contrast enhancement, adjust brightness,sharpening, re-sample etc.

� Image restoration: Undoing a degradation process of theimage. We will study Linear Shift Invariant (LSI) degradationsystems only, for eg: Camera impulse response, Motion bluretc.

� Compression: A standard gray-scale image, let’s say1024 × 1024 pixels, without compression will require about 1MB memory! We will study some lossy and losslesscompression schemes including the well-known JPEG scheme.

IT-523 DIP: Lecture 1 8/10

Course contents

Image acquisition - Image formation model, Sampling,Intensity quantization.

Terminology related to an image: Pixel, Neighborhood,connectivity etc.

Processing:� Image Enhancement (Pre-processing): Goal is to make the

image more conducive to further processing or viewing.Noise removal, Contrast enhancement, adjust brightness,sharpening, re-sample etc.

� Image restoration: Undoing a degradation process of theimage. We will study Linear Shift Invariant (LSI) degradationsystems only, for eg: Camera impulse response, Motion bluretc.

� Compression: A standard gray-scale image, let’s say1024 × 1024 pixels, without compression will require about 1MB memory! We will study some lossy and losslesscompression schemes including the well-known JPEG scheme.

IT-523 DIP: Lecture 1 8/10

Course contents

Image acquisition - Image formation model, Sampling,Intensity quantization.

Terminology related to an image: Pixel, Neighborhood,connectivity etc.

Processing:� Image Enhancement (Pre-processing): Goal is to make the

image more conducive to further processing or viewing.Noise removal, Contrast enhancement, adjust brightness,sharpening, re-sample etc.

� Image restoration: Undoing a degradation process of theimage. We will study Linear Shift Invariant (LSI) degradationsystems only, for eg: Camera impulse response, Motion bluretc.

� Compression: A standard gray-scale image, let’s say1024 × 1024 pixels, without compression will require about 1MB memory! We will study some lossy and losslesscompression schemes including the well-known JPEG scheme.

IT-523 DIP: Lecture 1 8/10

Course contents

� Segmentation: Find the object of interest in a given image.

� Morphological Processing: Nonlinear processing based onset-theoretic concepts. Used for preprocessing and description.

� Representation & Description: How to represent objects in animage such that the description can be used to identify otherinstances of the same object.

From the book:

Chapters 2,3,4,5,8,9,10,11

IT-523 DIP: Lecture 1 9/10

Course contents

� Segmentation: Find the object of interest in a given image.

� Morphological Processing: Nonlinear processing based onset-theoretic concepts. Used for preprocessing and description.

� Representation & Description: How to represent objects in animage such that the description can be used to identify otherinstances of the same object.

From the book:

Chapters 2,3,4,5,8,9,10,11

IT-523 DIP: Lecture 1 9/10

Course contents

� Segmentation: Find the object of interest in a given image.

� Morphological Processing: Nonlinear processing based onset-theoretic concepts. Used for preprocessing and description.

� Representation & Description: How to represent objects in animage such that the description can be used to identify otherinstances of the same object.

From the book:

Chapters 2,3,4,5,8,9,10,11

IT-523 DIP: Lecture 1 9/10

Course contents

� Segmentation: Find the object of interest in a given image.

� Morphological Processing: Nonlinear processing based onset-theoretic concepts. Used for preprocessing and description.

� Representation & Description: How to represent objects in animage such that the description can be used to identify otherinstances of the same object.

From the book:

Chapters 2,3,4,5,8,9,10,11

IT-523 DIP: Lecture 1 9/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10

Research in DIP & related areas

Research in DIP has picked up a lot in the last 15 yrs or so due to:

Computational power

Lot of applications

People from other areas have started taking interest in DIP,especially applied mathematicians.

Take a look at recent issues of

Intl. Journal of Computer vision.

IEEE Transactions on Pattern Analysis and MachineIntelligence.

SIAM Journal on Imaging Science.

Journal of Mathematical Vision and Imaging.

IEEE Transactions on Image Processing.

IEEE Transactions on Medical Imaging.

Computer Vision & Image Understanding.

IT-523 DIP: Lecture 1 10/10