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详细解答机器视觉检测中图像处理的原理

时间:2017-12-05  来源:本文搜集于网络,由机器视觉检测设备厂家创盈时代整理,欢迎转载,转载请注明出处  点击:275

机器视觉检测中图像处理涵盖的范围十分很广泛,但是,所采用的基本原理和方法是一致的。整体说来,图像处理这门科学所研究的主要内容包括了图像数的模数转化、图像的增强与复原、图像编码与压缩、图像切割、图像的表示和描述、图像特征匹配等等。
The range of image processing covers a very wide range, but the basic principles and methods used are consistent. As a whole, the main contents of image processing science include modulus conversion, image enhancement and restoration, image coding and compression, image cutting, image representation and description, image feature matching and so on.

所谓切割就是企图将图像中之标的物析出的处理过程,图像切割可说是视觉检测设备图像的分析过程中最重要之步骤之一,在一般所采用的方法主要为边缘的检测及临界值法。

The so-called cutting is the process of trying to separate the object in the image. Image cutting is one of the most important steps in the process of image analysis. The commonly used methods are edge detection and critical value method.


机器视觉检测


图像特征匹配,特征匹配法的"特征",需先加以定义。举例而言,若要描述一个人,最好先说明他的特征。在外表方面,例如身高、体重、胸围....等等;在心理方面,例如和善的、好胜的、沉默的....等等;在事业方面,例如职业、收入....等等。不同特征适用于不同描述目的,例如描述一个人的健康,需要上述的身高、体重特征;若要描述一个人的成就,所需特征就多得多,举凡上述特征之外,还可能需要这个人的生平事迹等等。据此了解,一个人的特征能够代表一个人,故特征具备了代表性。除外,若现需将每个人由高至矮排序,所需特征只身高一项,其它体重、性格等等数据无需获得,因此使用特征亦具备简化使用信息量之目的。
The feature matching of the image and the feature of the feature matching method should be defined first. For example, if a person is to be described, it is best to explain his features first. In appearance, such as height, weight, chest circumference.... and so on; in the psychological aspect, such as kind and competitive, silent... Etc..; in business, such as occupation, income... And so on. Different characteristics for different purpose, such as to describe a person's health needs, height and weight of the above; if you want to describe a person's achievements and characteristics needed much more, besides all the features mentioned above, may also need this person's life story and so on. According to this, the characteristics of a person can represent a person, so the characteristics are representative. Besides, if we need to rank each person from high to low, only one height is required. Other weight, character and other data do not need to be obtained. Therefore, the use of features also has the purpose of simplifying the use of information.

所谓匹配或被翻译成比对,即将物体的特征与预存在视觉检测设备中之原型或样版的特征加以比较,若相似度或非相似度小于或大于某预设的门槛值,则称两者匹配成功。匹配较倾向属于图形辨认范围,因其中含有分类或辨认意味之故。
Matching or being translated into comparison, the characteristics of objects are compared with those of prototypes or patterns in pre existing computers. If the similarity or non similarity is less than or larger than a preset threshold value, the match is successful. A matching tendency belongs to the scope of recognition, because it contains a classification or identification meaning.

建立视觉检测设备中原型或样版特征之过程称训练,做法为事先采取某些样品或典型之特征加以储存之。特征匹配的常用方法有许多种:最近邻居法、二元决策树法、属于动态规画法的DP匹配法等。
The process of establishing the characteristics of a prototype or sample plate in a computer is called training, which is stored in advance with certain samples or typical features. There are many kinds of feature matching method: nearest neighbor method, decision tree method, which belongs to the two yuan dynamic programming method DP matching method.

特征匹配目的在使具有相同或类似待征的物体产生关联,以便于辨认或分类。就交通方面而言,特征匹配法可用来区分不同的交通工具。举例而言,若图像中某物体长度4公尺,宽2公尺,形状呈矩形(以上皆为特征),该物体极可能被分类为小汽车;若为长10公尺,宽2.5公尺的矩形,则可被分类为大型车(巴士、大货车)。
The purpose of feature matching is to make associations with the same or similar objects to be identified so as to facilitate identification or classification. As far as traffic is concerned, the feature matching method can be used to distinguish different traffic tools. For example, if an object in the image is 4 meters long, 2 meters wide, and the shape is rectangular (all the above features), the object can be classified as a car. If it is 10 meters long and 2.5 meters wide, it can be classified as a large vehicle (bus or truck).

以上就是关于机器视觉检测过程中图像处理的基本原理介绍,深圳市创盈时代科技有限公司是一家专注于机器视觉,视觉检测设备,CCD光学检测设备,机器视觉检测,视觉方案定制,非标自动化设备的研发生产和销售于一体的国家高新技术企业。

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