e-Book | Linda Shapiro - The University Of Washington  | Download 

How Computer Vision is Changing the Way We Interact with Technology | Link

How do you test and improve computer vision algorithms?  | Link

SAP  | Download 

GBPP | Download 

Chapter 1 . 

• Introduction to computer vision

Chapter 2 .  

•  What is computer vision,

• Why computer vision, 

• Manfaat dan guna computer science. 

• History of computer vision

Chapter 3 .  

• Image gradient and edge 

• Edge detection, convulotion, what cause edge,gausian, dan laplacian 

Chapter 4 .  

• Proyeksi

• Proyeksi Perspektif

• Proyeksi Affine

• Proyeksi Spherica

Chapter 5 .  

• Sensor Kamera

• Kamera CCD

• Model Sensor

• Warna

• Kuantitas Spektral

• Persepsi Mata

• Representasi Warna

Chapter 6 .  

• Mengkaji berbagai algoritma tracking

• Mendemokan dan mensimulasikan berbagai algoritma tracking

• contoh image traking dan filtering dalam kehidupan sehari-hari. 

Chapter 7 .  

• Linier filtering, image formation, digital images, image noise, image filtering.

• Edge and binary image analysis

• Edge detection, canny detector, sobel detector, thresholding

Chapter 8 .  

• Texture

• Chamfer matching system, 

• analysis and syntetis, 

• texture analysis.

Chapter 9 .  

• Color

• Color and light, 

• what is color, 

• color matching, 

• measuring color, 

• distance color.

Chapter 10  :  transformation dan geomatric transformation 

• Image transformations

• Grey level transformations.

• Histogram equalization.

• Geometric transformations.

• Affine transformations.

• Polynomial warps 

Chapter 11  :  

• Face detection and Recognition 

Chapter 12  :  image morphology 

• Morphological operation

• Erode and dilate as max and min operators on binary images.

• Open, close, thinning and other transforms.

• Medial axis transform.

• Introduction to grey-level morphology.

Chapter 13  :  Filtering 

• Image filtering

• Fourier descriptors.

• Linear and non-linear filtering operations.

• Image convolutions.

• Separable convolutions.

• Sub-sampling and interpolation as convolution operations 

Chapter 14  :  Region of interest dan image boundary 

• Feature characterisation

• Calculation of region properties.

• Moment features.

• Boundary coding line descriptors from boundary coding and from moments.

• Image search and multi-resolution algorithms.

Chapter 15  :   Edge detection

• Edge and corner detection

• Edge enhancement by differentiation.

• Effect of noise, edge detection and Canny implementation.

• Edge detector performance evaluation.

• Image structure tensor.

• Relationship to image auto-correlation.

• Characterisation and Harris corner detector 

• Chapter 16  :  image colopr representation

• Colour images :  IGI Global  | Article | 

• Representations of colour in digital images.

• Colour metrics.

• Pixel-wise (point) operations.

• Colour invariants and Finlayson colour constancy algorithm 

Chapter 16  :  Content based image rerieval 

• Template matching and advanced topics

• Similarity and dissimilarity matching metrics.

• L2 metric and relationship to cross-correlation2D object detection, recognition, location. 

• Practice : Membuat script dengan Matlab untuk CBIR

Journal :
1. Content Based Image Retrieval Berdasarkan Fitur Bentuk Menggunakan Metode Gradien Vector Slow Snake | Download

 2.   Aplikasi Content-based Image Retrieval (CBIR) dengan Octave | Youtube