ŶŮŢŨŢŻŪůŦġŪŴŴŶŦġljĸ ĵķ In the following, I will brie"y discuss how edge detection can be used in the Macao society. License plate detection: Today, cars are everywhere. Intelligent tra%c control will no doubt become the future trend. So I will brie"y discuss how we can apply edge detection in license plate detection. License plate detection technology is widely used in tollgates as well as parking lots in public places, companies, and residential areas. So improving this technology is of great practical value. First we conducted sample image gray scaling and QDPA operator edge detection. Below is a comparison of the two images (take this vehicle as an example) Detecting hidden information in medical images: What distinguishes our phase-based detection methods from traditional edge detection methods such as Canny and Sobel is that we not only can detect the edges of an object; we can also detect some hidden information of the test object. It is impossible for these details to be detected via traditional methods because there is very little di#erence between the colour of these details and the colour of their surrounding regions. ŔŰŤŪŢŭġłűűŭŪŤŢŵŪŰůŴġŰŧġ ņťŨŦġŅŦŵŦŤŵŪŰů 医学图像中检测隐藏的资讯Ȉ ا েᅹൄ 的ह֜ ᕭเ的ў ޱ 的־ሃཇ፡ᕭเȞCanny、 Sobelȟў ޱ 的ᢖᔹᙇ࣏， ا েЙକᕭเ ߏ ᢜ的፡，ϵҞѽᕭเ ߏ ᢜ的Ϙ ڱ ᘳ的Ⴄୈ， ഺ ڱ ြԯऎሃ۹ඛா的ᛞ֒ ਮಳ࢝Ј，ཇ 的ў ޱ ࣏๑ ޱ ᕭเҍ ڽ 的Ȟ ڍ ᄦĵȟ。 ൌ )LJXUH 是ᑥᴿ䲦ᖧ的人儊㛓㠕的&7ൌ，ᗔቃ∊ൌⵁࡦ，ᡇ ه 的方⌋ 最 ᗂ的пᑻൌ ，ਥԛᴿ᭾的⃘ ③出㛓㠕的䲦ᖧ䜞࠼，ެ 中4'3$的⃘ ③᭾᷒ 是最⨼ᜩ的。 CT images of a human liver. We can see from the last three images that our methods can effectively detect the shaded regions of the liver, and among these methods, QDPA performed the best. 儎▊⅙教授ૂ ঐ༡⭕㜗ਾ֒ 的䄌文Ʌะ᯲փ的䛀㐙⃘ ③㇍⌋Ɇ，ᨆ出Ҽ⭞փ⃘ ③ᖟ㢨ൌ܅䛀㐙的ࢫ新方⌋，ࣖрᴿ᭾ 的ሜ傍㎆᷒ ，ֵ ᗍ㜗在 &G, 䴱㞜ൌ܅會䆦р⦨ᗍ䄌文最֩ 㺞⨴⦄。 Phase-based Edge Detection Algrothms, a paper co-authored by Prof Kou Kit Ian and her PhD student Hu Xiaoxiao, received the ENGAGE 2017 Best Presentation Award at the Computer Graphics International. The paper proposes an innovative method for detecting the edges of colour images with PHASE). ɇ學院ሾ℺Ɉ ޝ ᇯ ۻ 代㺞֒ 㘻 ف 人ᝅ㿁 The views expressed in Faculty Column are solely those of the authors, and do not necessarily reflect the views of umagazine or UM.
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