it-e-66 Introduction to Digital Image Processing

An image is digitized to convert it to a form that can be stored in a computer's memory or on

some form of storage media such as a hard disk or CD-ROM. This digitization procedure can be
done by a scanner, or by a video camera connected to a frame grabber board in a computer. Once an
image has been digitized, it can be operated upon by various image processing operations.
Image processing operations can be roughly divided into three major categories, Image
Compression, Image Enhancement and Restoration, and Measurement Extraction[提取尺寸]. Image
compression is familiar to most people. [1]It involves reducing the amount of memory needed to
store a digital image.
Image defects which could be caused by the digitization process or by faults in the imaging
set-up (for example, bad lighting) can be corrected using Image Enhancement techniques. Once
the image is in good condition, the Measurement Extraction operations can be used to obtain
useful information from the image.
Some examples of Image Enhancement and Measurement Extraction are given below. The
examples shown all operate on 256 grey-scale images. This means that each pixel in the image is
stored as a number between 0 to 255, where 0 represents a black pixel, 255 represents a white
pixel and values in-between represent shades of grey. These operations can be extended to
operate on colour images.
The examples below represent only a few of the many techniques available for operating on
images. Details about the inner workings of the operations have not been given.
Image Enhancement and Restoration
The image at the left of Figure 1 has been corrupted image
by noise during the digitization process. The "clean"
image at the right of Figure 1 was obtained by applying a
median filter [中值滤波器]to the image.
An image with poor contrast, such as the one at
the left of Figure 2, can be improved by adjusting the
image histogram to produce the image shown at the
right of Figure 2.

 image
The image at the top left of Figure 3 has a corrugated effect due to a fault in the acquisition
process. This can be removed by doing a 2-dimensional Fast-Fourier Transform[快速傅里叶变换] on the image
(top right of Figure 3), removing the bright spots (bottom left of Figure 3), and finally doing an
inverse Fast Fourier Transform to return to the original image without the corrugated background
  (bottom right of Figure 3).

image

An image which has been captured in poor lighting conditions, and shows a continuous
change in the background brightness across the image (top left of Figure 4) can be corrected
using the following procedure. First remove the foreground objects by applying a 25 by 25
greyscale dilation operation (top right of Figure 4). Then subtract the original image from the
background image (bottom left of Figure 4). Finally invert the colors and improve the contrast by
adjusting the image histogram (bottom right of Figure 4).

image

The example below demonstrates how one could go about extracting measurements from an
image. The image at the top left of Figure 5 shows some objects. The aim is to extract information
about the distribution of the sizes (visible areas) of the objects. The first step involves segmenting
the image to separate the objects of interest from the background. This usually involves
thresholding the image, which is done by setting the values of pixels above a certain threshold value
to white, and all the others to black (top right of Figure 5). Because the objects touch, thresholding
at a level which includes the full surface of all the objects does not show separate objects. This
problem is solved by performing a watershed separation on the image (lower left of Figure 5). The
image at the lower right of Figure 5 shows the result of performing a logical AND of the two
images at the left of Figure 5. This shows the effect that the watershed separation has on touching
objects in the original image. Finally, some measurements can be extracted from the image.

image

frame grabber board  帧中继访问设备

 

1, corrugated  ['kɔrəgeitid]
a. 缩成皱纹的,使起波状的

2, dilation  [dai'leiʃən, di-]
n. 扩张,扩大;膨胀;详述

3, subtract  [səb'trækt]
v. 减去,扣掉,减少

4, segmenting  
n. 分段

5, thresholding  
n. 阈值转换法;域值

6, watershed  ['wɔ:təʃed, 'wɔ-]
n. (美)流域;分水岭;集水区;转折点
adj. 标志转折点的

Continue reading it-e-66 Introduction to Digital Image Processing

it-e-65 Convert a Graphics Format

Why change vectors to bitmaps?
Most of the clip art gallery is vector-based and will need to be converted into bitmap formats
(GIF) prior to putting it on the Web.
Why change bitmaps to vectors?
You will need to change vectors to bitmaps to perform tasks from the Drawing toolbar on a
bitmap picture (such as animate parts of a bitmap picture) you will need to convert it into a vector
format. You can then e.g. ungroup it and apply animations to only parts of it.
Which graphic converter to use?
To change your graphics format, you need to use a graphics converter. A popular graphics
editor you can use for this is Paint Shop Pro. Another graphics editor you can use is Adobe
PhotoShop, which is said to be the best one for this kind of conversion.
How to use your graphic converter?
Open your file in the graphics editor chosen: Select File | Open.
Select File | Save As.
Rename your file and choose a new format. For a bitmap to vectors conversion select the
WMF format. For the opposite conversion, select the GIF format if you have PowerPoint 97,
otherwise select JPEG or TIFF.
Unfortunately, some of the quality may be lost in the switch. MS office also provides
graphics converters.

Continue reading it-e-65 Convert a Graphics Format

phprpc初步

官网:

http://phprpc.org/

java只有源代码,不过包含了个make.bat运行后就生成了三个jar包,服务端只需要phprpc.jar,客户端需要phprpc_client.jar,不需要别的依赖包,very nice,那个phprpc_spring.jar的包尚不知是做什么用的。

服务端,自定义接口:

>package kzg.phprpc.hello.api;

Continue reading phprpc初步

it-3-64 Course Description

This course is an introduction to the basic concepts as well as applications of the rapidly
emerging field of digital image processing. It familiarizes the audience with the understanding,
design, and implementation of algorithms in the various subareas of digital image processing
such as image enhancement, image deblurring, image understanding, image security, and image
compression. Over 200 image examples complement the technical descriptions.
Benefits/Learning Objectives
This course will enable you to
explain the fundamental concepts and terminologies employed in digital imaging such as
sampling and aliasing, perceptual quantization; filtering, look-up tables, image histogram,
etc;

explain the various techniques used in image enhancement for contrast manipulation (e.g.,
histogram equalization), sharpening (e.g., unsharp masking) and noise removal (e.g.,
selective averaging, median filtering);
briefly demonstrate the performance of image deblurring algorithms such as inverse filtering
and Wiener filtering by using image examples;
briefly demonstrate the concepts behind digital signatures for image authentication and
invisible watermarking for image copyright protection;
briefly describe the current research topics in image understanding and demonstrate related
algorithm performances using image examples;
explain the basic technologies that serve the existing JPEG and the emerging JPEG2000
standards.
Intended Audience
Scientists, engineers, and managers who need to understand and/or apply the fundamental
concepts and techniques employed in digital image processing. Although no particular background is
needed, some prior knowledge of linear system theory (e.g., Fourier transforms) would be helpful.

1, deblurring  
n. [计] 去模糊
v. 由模糊变清晰;擦掉…的污点(deblur的ing形式)

2, histogram  ['histəugræm]
n. 柱状图
[计算机] 直方图

3, perceptual  [pə'septjuəl]
a. 感性的,知觉的

4, quantization  [,kwɔntai'zeiʃən]
量子化,数字化

5, Fourier  ['furiei]
n. 傅里叶

Continue reading it-3-64 Course Description

phprpc,xml,json,hessian 协议?

找到了关于几种序列化与反序列化的比较:

http://phprpc.group.iteye.com/group/wiki/1489-net-in-php-binary-soap-xml-json-hessian-serialization-such-as-the-efficiency-of-contrast

其中涉及到phprpc,xml,json,hessian。最后得出结论是phprpc最有效率。(这大概是做着自己写的文章,phprpc是国人作品。)

对于我喜欢的json,效率居然这样惨淡,真让我有点怀疑。但是细想一下,这里比较的宿主语言不是javascript,确实可能存在这个问题。

先到phprpc-java上面看看http://phprpc.org/zh_CN/docs/#[[PHPRPC%20for%20Java]]

哎呀终于找到组织了,淋漓精致的把webservice和“专家”们批判了一遍。看得我呵呵地笑。

看看hessian和phprpc http://www.iteye.com/topic/349461

这位仁兄已经搜罗了一大片:http://hi.baidu.com/liapiao/blog/item/6fe0e412565d8b15203f2e60.html

在我的观点来看,phprpc还需要在推广上加把力,一般正规项目的技术选型,都愿意选择有强大支持的组织。这一点上,phprpc(似乎由国内的一家公司开发)和hessian(由开发resin的公司caucho 开发)相比较那还要见仁见智了。

--------------

见我的

hessian实践:http://kazge.com/archives/450.html

phprpc实践:http://kazge.com/archives/452.html

--------------

综合考虑,虽然都不是银弹,但是我比较欣赏phprpc。

Continue reading phprpc,xml,json,hessian 协议?

Boolean.class 和 boolean.class

Boolean.class 和 boolean.class是一样的吗?答案是大大的NO:

Boolean.class.getCanonicalName()  -> “java.lang.Boolean”

boolean.class.getCanonicalName()  -> “boolean”

所以像这样的判断是不成立的:

true.isAssignableFrom(Boolean.class)

其它原始类型同理类推.

Continue reading Boolean.class 和 boolean.class

JDBC基础

在ORM上走,有时底下的都忘了。

1:一个connection是为之一个状态的,在未关闭它之前,前面的操作会影响后面的操作。例如,使用use语句,即使是不同的两个事务,前一个事务use abc;那么后面的事务是运行在数据库abc上。

2:connection是默认自动提交事务的,要实现类似begintransaction和endtransaction的逻辑,要在begintransaction里面setAutoCommit(false),在endtransaction里面setAutoCommit(true),提交使用commit,回滚使用rollback。记住,要是同一个connection。

3:不要想一个命令里执行多个语句,一个里面执行多条要看实际实现。推荐使用addBatch,或者是多个命令,每个命令只执行一条。

4:存在不能回滚的语句,例如在mysql中:

有些语句不能被回滚。通常,这些语句包括数据定义语言(DDL)语句,比如创建或取消数据库的语句,和创建、取消或更改表或存储的子程序的语句。
 

Continue reading JDBC基础

it-e-63 Concept of Graphics and Images

Image or Graphic? Technically, neither.[1]If you really want to be strict, computer pictures
are files, the same way WORD documents or solitaire games are files. They're all a bunch of ones
and zeros all in a row. But we do have to communicate with one another so let's decide.
Image. We'll use "image". That seems to cover a wide enough topic range.
"Graphic" is more of an adjective, as in "graphic format." we denote images on the Internet
by their graphic format. GIF is not the name of the image. GIF is the compression factors used to
create the raster format set up by CompuServe.
So, they're all images unless you're talking about something specific.
The images produced in Drawing programs (CorelDraw, Illustrator, Freehand, Designer etc)
are called vectorised graphics. [2]That is, all of the objects shown on the computer monitor are
representations of points and their relationship to each other on the work area, each of which is
stored in the computer as simple values and mathematical equations depicting: the relationship
between each point and the next point referenced to it, and the position (vector) of each point
referenced to a starting corner of the work area.
Bitmap pictures are stored as a vertical and horizontal array of Pixels and stored information
represents the colour of each of these pixels. The resolution of a bitmap picture describes how
many of these pixels exist over a set distance, usually horizontally: ie pixels per inch or pixels per
centimetre. An unaltered bitmap picture of 300 pixels / inch enlarged by 1000% will therefore
still have the same number of pixels across the actual picture area but each represented pixel will
cover a larger area.
[3]At such an enlargement, the picture would be of little use for reproduction unless viewed
from quite a long distance.
Bitmap or Photo-retouching programs are correctly called PAINTING PROGRAMS.
Vectorised drawings on the other hand can be enlarged as much as desired because, although the
above mentioned points on a drawing would be further apart, the relationship of any described line between
the points would always be the same. A single company logo file produced in a Drawing program could be
used for a business card, any brochure or poster, or plotting out to a Screen Print stencil 3 metres (9 feet)
wide, where as bitmap files would have to be created for every size used if practicable.
What is raster, vector, metafile, PDL, VRML, and so forth?
These terms are used to classify the type of data a graphics file contains.
Raster files (also called bitmapped files) contain graphics information described as pixels,
such as photographic images. Vector files contain data described as mathematical equations and

are typically used to store line art and CAD information. Metafiles are formats that may contain
either raster or vector graphics data. Page Description Languages (PDL) are used to describe the
layout of a printed page of graphics and text.
Animation formats are usually collections of raster data that is displayed in a sequence.
Multi-dimensional object formats store graphics data as a collection of objects (data and the code
that manipulates it) that may be rendered (displayed) in a variety of perspectives. Virtual Reality
Modeling Language (VRML) is a 3D, object-oriented language used for describing "virtual
worlds" networked via the Internet and hyperlinked within the World Wide Web. Multimedia file
formats are capable of storing any of the previously mentioned types of data, including sound and
video information.

1, deem  [di:m]
vt. 认为,视作;相信
vi. 认为,持某种看法;作某种评价

2, stems 
n. 茎(stem的复数);树管;阻挡物
v. 起源于(stem的三单形式);除去…的茎;给…装杆;止住
3, wiretap  ['waiə,tæp]
v.&n. 窃听或偷录,窃听情报,窃听装置
4, solitaire  ['sɔlitεə, ,sɔli'tεə]
n. 纸牌

5, denote  [di'nəut]
vt. 表示,指示

6, depict  [di'pikt]
vt. 描述;描画

7, brochure  [bro'ʃur]
n. 手册,小册子

8, plotting  ['plɔtiŋ]
n. 测绘;标图
v. [测] 绘图;密谋(plot的ing形式)

9, stencil  ['stensəl]
n. 模版,蜡纸
vt. 用蜡纸印刷;用模板印刷

10, raster  ['ræstə]
光栅,扫描线

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