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Lecture Digital image processing - Lecture 27: Image segmentation

This chapter presents the following content: Image segmentation by thresholding, global threshold, adaptive/dynamic threshold, local threshold, segmentation algorithms, discontinuity based segmentation link the edge points.

7/8/2020 3:05:18 PM +00:00

Lecture Digital image processing - Lecture 26: Image segmentation

This chapter presents the following content: Link the edge points, local processing, global processing, hough transformation, image analysis, image segmentation, segmentation algorithms, discontinuities intensity, gradient operators linking the edge points.

7/8/2020 3:05:11 PM +00:00

Lecture Digital image processing - Lecture 25: Image segmentation

This chapter presents the following content: pseudocolors image processing, full color image processing, image analysis, image segmentation, segmentation algorithms, discontinuities intensity, lines and edges, gradient operators, linking the edge points.

7/8/2020 3:05:05 PM +00:00

Lecture Digital image processing - Lecture 24: Color Images

This chapter presents the following content: RGB color model, CMY model, HSI color model, pseudocolors image processing, full color image processing, color characteristics, chromaticity diagram and its use, color models, RGB color model.

7/8/2020 3:04:59 PM +00:00

Lecture Digital image processing - Lecture 23: Color Images

This chapter presents the following content: Color image processing, primary and secondary colors, color characteristics, chromaticity diagram and its use, color models, rgb color model, image registration, different mismatch or measures, cross correlation between tow images, applications of image registration.

7/8/2020 3:04:53 PM +00:00

Lecture Digital image processing - Lecture 22: Image registration

This chapter presents the following content: Image registration, different mismatch or measures, cross correlation between tow images, applications of image registration, estimation of degradation model, restoration techniques.

7/8/2020 3:04:47 PM +00:00

Lecture Digital image processing - Lecture 21: Image restoration

This chapter presents the following content: Restoration techniques, inverse filtering, minimum mean square error (wiener), constrained least square filter, restoration in presence of periodic noise, estimation of degradation model, restoration techniques.

7/8/2020 3:04:41 PM +00:00

Lecture Digital image processing - Lecture 20: Image restoration

This chapter presents the following content: Image formation process and the degradation model, degradation model in continues function and its discrete formulation, discrete formulation for 1D and 2D, estimation of degradation model, by observation, by experimentation, mathematical model, restoration techniques.

7/8/2020 3:04:35 PM +00:00

Lecture Digital image processing - Lecture 19: Image restoration

This chapter presents the following content: Image restoration techniques, difference between image enchantment and image restoration, image formation process and the degradation model, degradation model in continues function and its discrete formulation, discrete formulation for 1D and 2D.

7/8/2020 3:04:29 PM +00:00

Lecture Digital image processing - Lecture 18: Image Enhancement

This chapter presents the following content: Frequency domain filters, ideal lowpass filters, butterworth highpass filters, gaussian highpass filters, the laplacian in the frequency domain, high boost filtering, homomorphic filtering.

7/8/2020 3:04:23 PM +00:00

Lecture Digital image processing - Lecture 17: Image Enhancement

This chapter presents the following content: Sharpening, 1st and 2nd order derivatives, laplacian filter, unsharp masking and high-boost filtering, First order derivatives using the gradient operator, shobel operator using first order derivatives, what are edges in image? modeling intensity changes, steps of edge detection.

7/8/2020 3:04:16 PM +00:00

Lecture Digital image processing - Lecture 16: Image enhancement

This chapter presents the following content: 1st and 2nd order derivatives, laplacian filter, unsharp masking and high-boost filtering, mask processing, linear smoothing operation, median filter, sharpening spatial filter.

7/8/2020 3:04:10 PM +00:00

Lecture Digital image processing - Lecture 15: Image enhancement

This chapter presents the following content: Image differencing, averaging of the images, mask processing, linear smoothing operation, mask processing, linear smoothing operation, median filter, sharpening spatial filter.

7/8/2020 3:04:04 PM +00:00

Lecture Digital image processing - Lecture 14: Image Enhancement

This chapter presents the following content: The global information of the image with the help of histogram, histogram based techniques, image differencing, averaging of the images, mask processing, linear smoothing operation.

7/8/2020 3:03:58 PM +00:00

Lecture Digital image processing - Lecture 13: Image Enhancement

After studying this chapter you will be able to understand: The global information of the image with the help of histogram, histogram based techniques, histogram equalization, histogram specification or also known as histogram matching or histogram modification.

7/8/2020 3:03:52 PM +00:00

Lecture Digital image processing - Lecture 12: Image enhancement

After studying this chapter you will be able to understand: Necessity of image enhancement, image enhancement techniques broad categories, one of the category is spatial domain operations In spatial domain operations, frequency domain operations.

7/8/2020 3:03:46 PM +00:00

Lecture Digital image processing - Lecture 11: Image Transformation

After studying this chapter you will be able to understand: Analyze the computational complexity of image transform operations, the separable transformation, computational complexity reduction of the separable transformation.

7/8/2020 3:03:40 PM +00:00

Lecture Digital image processing - Lecture 10: Interpolation

After studying this chapter you will be able to understand: Why and when, do we need image interpolation and image resampling; interpolation operation; algorithms for different image transformations and the needed interpolation operation; image interpolation explanation; interpolation operation; unitary matrix and its equation.

7/8/2020 3:03:34 PM +00:00

Lecture Digital image processing - Lecture 9: Interpolation and Resampling

After studying this chapter you will be able to understand: Fundamentals of computer graphics third edition by peter shirley and steve marschner, interactive computer graphics, a top-down approach with OpenGL (Sixth Edition) by Edward Angel.

7/8/2020 3:03:28 PM +00:00

Lecture Digital image processing - Lecture 8: Camera Calibration and Stereo Imaging

After studying this chapter you will be able to understand: described how memory stores data, instructions, and information, and discussed the sequence of operations that occur when a computer executes an instruction. The chapter included a comparison of various microprocessors on the market today.

7/8/2020 3:03:22 PM +00:00

Lecture Digital image processing - Lecture 7: Camera Model and Imaging Geometry

After studying this chapter you will be able to understand: Inverse perspective transformation, imaging geometry where the world coordinate system and the camera coordinate system, what are the transformations steps involved in a generalized imaging setup, illustrate the concept with the help of an example.

7/8/2020 3:03:16 PM +00:00

Lecture Digital image processing - Lecture 6: Transformations

After studying this chapter you will be able to understand: Different distance measures, application of distance measures, arithmetic and logical operations on images, neighborhood operation on images, some basic mathematical transformations, the inverse transformations of these different mathematical transformations.

7/8/2020 3:03:10 PM +00:00

Lecture Digital image processing - Lecture 5: Relationships of Pixel

After studying this chapter you will be able to understand: Pixel connectivity, what is adjacency, different types of adjacency, connected component labeling problem, component leveling algorithm, different distance measures, application of distance measures, arithmetic and logical operations on images, neighborhood operation on images.

7/8/2020 3:03:04 PM +00:00

Lecture Digital image processing - Lecture 4: Pixels

After studying this chapter you will be able to understand: By representing the image in matrix with different points called “pixels”, there are some important relationships exist among those pixels, neighborhood of the pixel and there types, connectivity in an image, connected component labeling algorithm, adjacency and different types of adjacency relationships, distance measures method, different image operations.

7/8/2020 3:02:58 PM +00:00

Lecture Digital image processing - Lecture 3: Image Digitization 2

After studying this chapter you will be able to understand: Frequency spectrum of an image, explain the sampling of the 2 dimension image, the second stage of the digitization process, in the first sampling and in the second quantization of each of the samples, optimum mean square error or lloyd-max quantizer, designing of an optimum quantizer with the given signal probability density function.

7/8/2020 3:02:51 PM +00:00

Lecture Digital image processing - Lecture 2: Image Digitization I

After studying this chapter you will be able to understand: Need for the digitization, to digitize the image, sampling, quantization, how to digitize an image? Why do we need to digitization? What is digitization? How to digitize an image?

7/8/2020 3:02:45 PM +00:00

Lecture Digital image processing - Lecture 1: Introduction to Digital Image Processing

This lecture covers the fundamental concepts related to digital images and their processing. Topics covered include image processing fundamentals, image pre-processing, image segmentation, image compression, image representation, image description and object recognition.

7/8/2020 3:02:38 PM +00:00

Áp dụng kỹ thuật phân vùng không gian cho mô phỏng khói trong thực tại ảo

Bài viết nghiên cứu, đề xuất áp dụng kỹ thuật phân vùng không gian cho mô phỏng khói trong thực tại ảo. Nhóm tác giả tiến hành cài đặt các thuật toán mô phỏng khói, đánh giá các kết quả thu được khi mô phỏng khói với kỹ thuật Particle và kỹ thuật Particle kết hợp phân vùng không gian trong thực tại ảo.

7/8/2020 12:21:45 PM +00:00

Giải pháp nâng cao chất lượng giữa đào tạo thiết kế đồ họa và doanh nghiệp trong tình hình hiện nay

Bài viết bước đầu đưa ra phác thảo, luận giải về giải pháp nâng cao, đổi mới chất lượng đào tạo thiết kế đồ họa ở Việt Nam hiện nay, đồng thời đề cao vai trò của các doanh nghiệp (nơi tiếp nhận đầu ra cho các cơ sở đào tạo nguồn nhân lực về thiết kế).

7/8/2020 11:31:52 AM +00:00

Mốc son và thách thức mới của đào tạo ngành design

Lịch sử ngành đào tạo mỹ thuật công nghiệp (MTCN) trên thế giới đã tròn trăm năm với sự ra đời của Bauhaus, tại Việt Nam cũng đã tồn tại 70 năm. Ngành design của thế giới đã chuyển qua rất nhiều cấp độ phát triển về lý thuyết và thực hành.

7/8/2020 11:31:40 AM +00:00