본문내용 바로가기
무료배송 소득공제

Feature Extraction and Image Processing for Computer Vision

0004/E | Paperback
Mark S. Nixon 지음 | Academic Press | 2020년 01월 01일
  • 정가 : 110,000원
    판매가 : 110,000 [0%↓ 0원 할인] 할인쿠폰 받기
  • 통합포인트 :
    [기본적립] 3,300원 적립 [3% 적립] [추가적립] 5만원 이상 구매 시 2천원 추가적립 안내 [회원혜택] 실버등급 이상, 3만원 이상 구매 시 2~4% 추가적립 안내
  • 추가혜택 : 포인트 안내 도서소득공제 안내 추가혜택 더보기
  • 배송비 : 무료 배송비 안내
  • 배송일정 : 서울특별시 종로구 세종대로 기준 지역변경
    04월 07일 출고 예정 배송일정 안내

알립니다.

  • 외국도서의 경우 해외제공정보로만 서비스되어 미표기된 정보가 있을 수 있습니다. 필요한 정보가 있을경우 1:1 문의게시판 을 이용하여 주십시오.
상품상세정보
ISBN 9780128149768(0128149760)
쪽수 626쪽
언어 English
크기 191(W) X 235(H) X 33(T) (mm)
0004/E
제본형태 페이퍼백-Paperback
총권수 1권

책소개

이 책이 속한 분야

목차

Preface

1. Introduction

1.1 Overview

1.2 Human and computer vision

1.3 The human vision system

1.3.1 The eye

1.3.2 The neural system

1.3.3 Processing

1.4 Computer vision systems

1.4.1 Cameras

1.4.2 Computer interfaces

1.5 Processing images

1.5.1 Processing

1.5.2 Hello Python, hello images!

1.5.3 Mathematical tools

1.5.4 Hello Matlab

1.6 Associated literature

1.6.1 Journals, magazines and conferences

1.6.2 Textbooks

1.6.3 The web

1.7 Conclusions

References

2. Images, sampling and frequency domain processing

2.1 Overview

2.2 Image formation

2.3 The Fourier Transform

2.4 The sampling criterion

2.5 The discrete Fourier Transform

2.5.1 One-dimensional transform

2.5.2 Two-dimensional transform

2.6 Properties of the Fourier Transform

2.6.1 Shift invariance

2.6.2 Rotation

2.6.3 Frequency scaling

2.6.4 Superposition (linearity)

2.6.5 The importance of phase

2.7 Transforms other than Fourier

2.7.1 Discrete cosine transform

2.7.2 Discrete Hartley Transform

2.7.3 Introductory wavelets

2.7.3.1 Gabor Wavelet

2.7.3.2 Haar Wavelet

2.7.4 Other transforms

2.8 Applications using frequency domain properties

2.9 Further reading

References

3. Image processing

3.1 Overview

3.2 Histograms

3.3 Point operators

3.3.1 Basic point operations

3.3.2 Histogram normalisation

3.3.3 Histogram equalisation

3.3.4 Thresholding

3.4 Group operations

3.4.1 Template convolution

3.4.2 Averaging operator

3.4.3 On different template size

3.4.4 Template convolution via the Fourier transform

3.4.5 Gaussian averaging operator

3.4.6 More on averaging

3.5 Other image processing operators

3.5.1 Median filter

3.5.2 Mode filter

3.5.3 Nonlocal means

3.5.4 Bilateral filtering

3.5.5 Anisotropic diffusion

3.5.6 Comparison of smoothing operators

3.5.7 Force field transform

3.5.8 Image ray transform

3.6 Mathematical morphology

3.6.1 Morphological operators

3.6.2 Grey level morphology

3.6.3 Grey level erosion and dilation

3.6.4 Minkowski operators

3.7 Further reading

References

4. Low-level feature extraction (including edge detection)

4.1 Overview

4.2 Edge detection

4.2.1 First-order edge detection operators

4.2.1.1 Basic operators

4.2.1.2 Analysis of the basic operators

4.2.1.3 Prewitt edge detection operator

4.2.1.4 Sobel edge detection operator

4.2.1.5 The Canny edge detector

4.2.2 Second-order edge detection operators

4.2.2.1 Motivation

4.2.2.2 Basic operators: The Laplacian

4.2.2.3 The Marr?Hildreth operator

4.2.3 Other edge detection operators

4.2.4 Comparison of edge detection operators

4.2.5 Further reading on edge detection

4.3 Phase congruency

4.4 Localised feature extraction

4.4.1 Detecting image curvature (corner extraction)

4.4.1.1 Definition of curvature

4.4.1.2 Computing differences in edge direction

4.4.1.3 Measuring curvature by changes in intensity (differentiation)

4.4.1.4 Moravec and Harris detectors

4.4.1.5 Further reading on curvature

4.4.2 Feature point detection; region/patch analysis

4.4.2.1 Scale invariant feature transform

4.4.2.2 Speeded up robust features

4.4.2.3 FAST, ORB, FREAK, LOCKY and other keypoint detectors

4.4.2.4 Other techniques and performance issues

4.4.3 Saliency

4.4.3.1 Basic saliency

4.4.3.2 Context aware saliency

4.4.3.3 Other saliency operators

4.5 Describing image motion

4.5.1 Area-based approach

4.5.2 Differential approach

4.5.3 Recent developments: deep flow, epic flow and extensions

4.5.4 Analysis of optical flow

4.6 Further reading

References

5. High-level feature extraction: fixed shape matching

5.1 Overview

5.2 Thresholding and subtraction

5.3 Template matching

5.3.1 Definition

5.3.2 Fourier transform implementation

5.3.3 Discussion of template matching

5.4 Feature extraction by low-level features

5.4.1 Appearance-based approaches

5.4.1.1 Object detection by templates

5.4.1.2 Object detection by combinations of parts

5.4.2 Distribution-based descriptors

5.4.2.1 Description by interest points (SIFT, SURF, BRIEF)

5.4.2.2 Characterising object appearance and shape

5.5 Hough transform

5.5.1 Overview

5.5.2 Lines

5.5.3 HT for circles

5.5.4 HT for ellipses

5.5.5 Parameter space decomposition

5.5.5.1 Parameter space reduction for lines

5.5.5.2 Parameter space reduction for circles

5.5.5.3 Parameter space reduction for ellipses

5.5.6 Generalised Hough transform

5.5.6.1 Formal definition of the GHT

5.5.6.2 Polar definition

5.5.6.3 The GHT technique

5.5.6.4 Invariant GHT

5.5.7 Other extensions to the HT

5.6 Further reading

References

6. High-level feature extraction: deformable shape analysis

6.1 Overview

6.2 Deformable shape analysis

6.2.1 Deformable templates

6.2.2 Parts-based shape analysis

6.3 Active contours (snakes)

6.3.1 Basics

6.3.2 The Greedy Algorithm for snakes

6.3.3 Complete (Kass) Snake implementation

6.3.4 Other Snake approaches

6.3.5 Further Snake developments

6.3.6 Geometric active contours (Level Set-Based Approaches)

6.4 Shape Skeletonisation

6.4.1 Distance transforms

6.4.2 Symmetry

6.5 Flexible shape models ? active shape and active appearance

6.6 Further reading

References

7. Object description

7.1 Overview and invariance requirements

7.2 Boundary descriptions

7.2.1 Boundary and region

7.2.2 Chain codes

7.2.3 Fourier descriptors

7.2.3.1 Basis of Fourier descriptors

7.2.3.2 Fourier expansion

7.2.3.3 Shift invariance

7.2.3.4 Discrete computation

7.2.3.5 Cumulative angular function

7.2.3.6 Elliptic Fourier descriptors

7.2.3.7 Invariance

7.3 Region descriptors

7.3.1 Basic region descriptors

7.3.2 Moments

7.3.2.1 Definition and properties

7.3.2.2 Geometric moments

7.3.2.3 Geometric complex moments and centralised moments

7.3.2.4 Rotation and scale invariant moments

7.3.2.5 Zernike moments

7.3.2.6 Tchebichef moments

7.3.2.7 Krawtchouk moments

7.3.2.8 Other moments

7.4 Further reading

References

8. Region-based analysis

8.1 Overview

8.2 Region-based analysis

8.2.1 Watershed transform

8.2.2 Maximally stable extremal regions

8.2.3 Superpixels

8.2.3.1 Basic techniques and normalised cuts

8.2.3.2 Simple linear iterative clustering

8.3 Texture description and analysis

8.3.1 What is texture?

8.3.2 Performance requirements

8.3.3 Structural approaches

8.3.4 Statistical approaches

8.3.4.1 Co-occurrence matrix

8.3.4.2 Learning-based approaches

8.3.5 Combination approaches

8.3.6 Local binary patterns

8.3.7 Other approaches

8.3.8 Segmentation by texture

8.4 Further reading

References

9. Moving object detection and description

9.1 Overview

9.2 Moving object detection

9.2.1 Basic approaches

9.2.1.1 Detection by subtracting the background

9.2.1.2 Improving quality by morphology

9.2.2 Modelling and adapting to the (static) background

9.2.3 Background segmentation by thresholding

9.2.4 Problems and advances

9.3 Tracking moving features

9.3.1 Tracking moving objects

9.3.2 Tracking by local search

9.3.3 Problems in tracking

9.3.4 Approaches to tracking

9.3.5 MeanShift and Camshift

9.3.5.1 Kernel-based density estimation

9.3.5.2 MeanShift tracking 456

9.3.5.3 Camshift technique 461

9.3.6 Other approaches 465

9.4 Moving feature extraction and description 468

9.4.1 Moving (biological) shape analysis 468

9.4.2 Space?time interest points 470

9.4.3 Detecting moving shapes by shape matching in

image sequences 470

9.4.4 Moving shape description 474

9.5 Further reading 477

References 478

Contents xv

These proofs may contain color figures. Those figures may print black and white in the final printed book if a color print product has not been planned. The color figures will

appear in color in all electronic versions of this book.

To protect the rights of the author(s) and publisher we inform you that this PDF is an uncorrected proof for internal business use only by the author(s), editor(s), reviewer(s),

Elsevier and typesetter TNQ Books and Journals Pvt Ltd. It is not allowed to publish this proof online or in print. This proof copy is the copyright property of the publisher

and is confidential until formal publication.

10. Camera geometry fundamentals 483

10.1 Overview 483

10.2 Projective space 483

10.2.1 Homogeneous co-ordinates and projective

geometry 484

10.2.2 Representation of a line, duality and ideal points 485

10.2.3 Transformations in the projective space 487

10.2.4 Computing a planar homography 490

10.3 The perspective camera 493

10.3.1 Perspective camera model 494

10.3.2 Parameters of the perspective camera model 498

10.3.3 Computing a projection from an image 498

10.4 Affine camera

10.4.1 Affine camera model

10.4.2 Affine camera model and the perspective projection

10.4.3 Parameters of the affine camera model

10.5 Weak perspective model

10.6 Discussion

10.7 Further reading

References

11. Colour images

11.1 Overview

11.2 Colour image theory

11.2.1 Colour images

11.2.2 Tristimulus theory

11.2.3 The colourimetric equation

11.2.4 Luminosity function

11.3 Perception-based colour models: CIE RGB and CIE XYZ

11.3.1 CIE RGB colour model: Wright?Guild data

11.3.2 CIE RGB colour matching functions

11.3.3 CIE RGB chromaticity diagram and chromaticity co-ordinates

11.3.4 CIE XYZ colour model

11.3.5 CIE XYZ colour matching functions

11.3.6 XYZ chromaticity diagram

11.3.7 Uniform colour spaces: CIE LUV and CIE LAB

11.4 Additive and subtractive colour models

11.4.1 RGB and CMY

11.4.2 Transformation between RGB models

11.4.3 Transformation between RGB and CMY models

11.5 Luminance and chrominance colour models

11.5.1 YUV, YIQ and YCbCr models

11.5.2 Luminance and gamma correction

11.5.3 Chrominance

11.5.4 Transformations between YUV, YIQ and RGB colour models

11.5.5 Colour model for component video: YPbPr

11.5.6 Colour model for digital video: YCbCr

11.6 Additive perceptual colour models

11.6.1 The HSV and HLS colour models

11.6.2 The hexagonal model: HSV

11.6.3 The triangular model: HLS

11.6.4 Transformation between HLS and RGB

11.7 More colour models

References

12. Distance, classification and learning

12.1 Overview

12.2 Basis of classification and learning

12.3 Distance and classification

12.3.1 Distance measures

12.3.1.1 Manhattan and Euclidean Ln norms

12.3.1.2 Mahalanobis, Bhattacharrya and Matusita

12.3.1.3 Histogram intersection, Chi2 (c2) and the Earth Mover’s distance

12.3.2 The k-nearest neighbour for classification

12.4 Neural networks and Support Vector Machines

12.5 Deep learning

12.5.1 Basis of deep learning

12.5.2 Major deep learning architectures

12.5.3 Deep learning for feature extraction

12.5.4 Deep learning performance evaluation

12.6 Further reading

References

북로그 리뷰 (0) 쓰러가기

도서 구매 후 리뷰를 작성하시면 통합포인트를 드립니다.
결제 90일 이내 작성 시 300원 / 발송 후 5일 이내 작성시 400원 / 이 상품의 첫 리뷰 작성 시 500원
(포인트는 작성 후 다음 날 적립되며, 도서 발송 전 작성 시에는 발송 후 익일에 적립됩니다.
외서/eBook/음반/DVD/GIFT 및 잡지 상품 제외)
안내
  • 해당도서의 리뷰가 없습니다.

Klover 평점/리뷰 (0)

문장수집 (0) 문장수집 쓰기 나의 독서기록 보기
※구매도서의 문장수집을 기록하면 통합포인트 적립 안내

교환/반품/품절안내

※ 상품 설명에 반품/교환 관련한 안내가 있는 경우 그 내용을 우선으로 합니다. (업체 사정에 따라 달라질 수 있습니다.)

교환/반품/품절안내
반품/교환방법 마이룸 > 주문관리 > 주문/배송내역 > 주문조회 > 반품/교환신청 ,
[1:1상담>반품/교환/환불] 또는 고객센터 (1544-1900)

※ 오픈마켓, 해외배송주문, 기프트 주문시 [1:1상담>반품/교환/환불]
    또는 고객센터 (1544-1900)
반품/교환가능 기간 변심반품의 경우 수령 후 7일 이내,
상품의 결함 및 계약내용과 다를 경우 문제점 발견 후 30일 이내
반품/교환비용 변심 혹은 구매착오로 인한 반품/교환은 반송료 고객 부담
반품/교환 불가 사유
  • 소비자의 책임 있는 사유로 상품 등이 손실 또는 훼손된 경우
    (단지 확인을 위한 포장 훼손은 제외)
  • 소비자의 사용, 포장 개봉에 의해 상품 등의 가치가 현저히 감소한 경우
    예) 화장품, 식품, 가전제품(악세서리 포함) 등
  • 복제가 가능한 상품 등의 포장을 훼손한 경우
    예) 음반/DVD/비디오, 소프트웨어, 만화책, 잡지, 영상 화보집
  • 소비자의 요청에 따라 개별적으로 주문 제작되는 상품의 경우 ((1)해외주문도서)
  • 디지털 컨텐츠인 eBook, 오디오북 등을 1회 이상 다운로드를 받았을 경우
  • 시간의 경과에 의해 재판매가 곤란한 정도로 가치가 현저히 감소한 경우
  • 전자상거래 등에서의 소비자보호에 관한 법률이 정하는 소비자 청약철회 제한 내용에
    해당되는 경우
(1) 해외주문도서 : 이용자의 요청에 의한 개인주문상품으로 단순변심 및 착오로 인한 취소/교환/반품 시 ‘해외주문 반품/취소 수수료’ 고객 부담 (해외주문 반품/취소 수수료 : ①양서-판매정가의 12%, ②일서-판매정가의 7%를 적용)
상품 품절 공급사(출판사) 재고 사정에 의해 품절/지연될 수 있으며, 품절 시 관련 사항에 대해서는
이메일과 문자로 안내드리겠습니다.
소비자 피해보상
환불지연에 따른 배상
  • 상품의 불량에 의한 교환, A/S, 환불, 품질보증 및 피해보상 등에 관한 사항은
    소비자분쟁해결 기준 (공정거래위원회 고시)에 준하여 처리됨
  • 대금 환불 및 환불지연에 따른 배상금 지급 조건, 절차 등은 전자상거래 등에서의
    소비자 보호에 관한 법률에 따라 처리함

이 책의 해외주문가능도서
있습니다.

이 분야의 베스트

  • Forouzan
    43,000원
  • J. Duncan Glove...
    40,000원
  • Charles H. Roth...
    43,000원
  • Harris, David
    43,000원
  • King, K. N.
    40,000원
더보기+

이 분야의 신간

  • Pearl, Judea
    12,750원
  • Robert L. Norto...
    44,000원
  • Roger S. Pressm...
    42,000원
  • Domingos, Pedro
    15,380원
  • Luksa, Marko
    58,650원
더보기+

바로가기

  • 우측 확장형 배너 2
  • 우측 확장형 배너 2

최근 본 상품