Coretan Ketiga....
Ku mulakan dengan lafaz Bismillah..
Emm…ini sebenarnya coretan ketiga menulis dalam blog :)
Kali pertama, tak jadik! Tensionnnn….
Bukan apa…sebab yela…masa memula buat blog, perasaan gumbira tak terkata, tapi sebagai seorang muslim, aku mulakan dengan lafaz Alhamdulillah…tau2 bila paste…eh…tak jadik!..tensen..tensen….
Tu yang daalam coretan kedua, aku tulis merapu skit,
walhal coretan pertama ditulis dengan penuh hemah , dan ada ciri2 solehah lagi tuh…heheheh..perasan….
tapi....bila diuji skit (blog buat hal kut)…hilang sabar…tapi silapnya aku…
Sape suruh taip terus kat tempat tulis mesej tuh….patutnya taip tempat lain dulu (word @ notepad @ etc…)
Anyway, nih adalah coretan ketiga….
Aku nak story pasal practical algorithms for image analysis…. Nih lebih berguna for those yang ada ambik bidang(@subjek) computer vision @ image processing. Err... aku sekarang kat opis nih….rasa sejuk semacam…tu la…orang lain hari ahad duk releks kat umah….bukannya pergi opis…. Apa nak buat, suami tersayang dah suruh….buat keje kat opis…tapi aku rasa sat lagi aku nak ngadu kat dia…sini sejuk aaaa…heater tak idup! :( . Tapi sekarang hubby aku pi carboot sale…. So kena sabar skit
And utk itu, better aku story apa mende yang aku nak story nih…Sorry to say, bahasa aku rojak – English + malay.
Ok, practical algorithms for image analysis….
Before story lebih2,i think its better we start with some basics knowledge that we should have to know...Since, i gonna telling you about image analysis, you might ask me, what’s the difference between image analysis and image processing? Emmm.... how to explain...
ok, let add one more thing, which is image understanding, and see what [1] has been explaining as below;
* Image Processing : image in -> image out
* Image Analysis : image in -> measurements out
* Image Understanding : image in -> high-level description out
Could you understand what this guy trying to say?
Ok, macam nih, aku rasa, dalam computer vision ada 3 aspect yang perlu difahami oleh mereka yang ambik computer vision as they will be implementing those 3 things, which are, image processing, image analysis and image understanding. In general, those 3 things are playing with image as their input data but the output is different. Image processing takes an image as input but provide another image as the result. Example; take a colourful image (RGB), process it (say, threshold) and results are, it became a binary image (black for interested objects and white for background).
What about image analysis? Again, take an image as input data, process it (I think this usually involve maths formula such as Fourier Transform, Laplace Transform or etc), and the results are in numerical approach. I believe, the results are best performed in graph or table, well that way is easier to analyze, right?
And for the last part is image understanding. Remember, take an image as input data, and process it (usually identifies shape of the interest object in the image) and then recognize the shape and describe it. For example, the image shows a face of a person. Image understanding might describe where the location of the eyes, mouth, nose and etc of that person.
Ok, hubby aku nak ambik….hehehe…study kat rumah pulak…
And coretan seterusnya will be continue next week…
Ref :
[1] http://www.ph.tn.tudelft.nl/Courses/FIP/noframes/fip-.html
Emm…ini sebenarnya coretan ketiga menulis dalam blog :)
Kali pertama, tak jadik! Tensionnnn….
Bukan apa…sebab yela…masa memula buat blog, perasaan gumbira tak terkata, tapi sebagai seorang muslim, aku mulakan dengan lafaz Alhamdulillah…tau2 bila paste…eh…tak jadik!..tensen..tensen….
Tu yang daalam coretan kedua, aku tulis merapu skit,
walhal coretan pertama ditulis dengan penuh hemah , dan ada ciri2 solehah lagi tuh…heheheh..perasan….
tapi....bila diuji skit (blog buat hal kut)…hilang sabar…tapi silapnya aku…
Sape suruh taip terus kat tempat tulis mesej tuh….patutnya taip tempat lain dulu (word @ notepad @ etc…)
Anyway, nih adalah coretan ketiga….
Aku nak story pasal practical algorithms for image analysis…. Nih lebih berguna for those yang ada ambik bidang(@subjek) computer vision @ image processing. Err... aku sekarang kat opis nih….rasa sejuk semacam…tu la…orang lain hari ahad duk releks kat umah….bukannya pergi opis…. Apa nak buat, suami tersayang dah suruh….buat keje kat opis…tapi aku rasa sat lagi aku nak ngadu kat dia…sini sejuk aaaa…heater tak idup! :( . Tapi sekarang hubby aku pi carboot sale…. So kena sabar skit
And utk itu, better aku story apa mende yang aku nak story nih…Sorry to say, bahasa aku rojak – English + malay.
Ok, practical algorithms for image analysis….
Before story lebih2,i think its better we start with some basics knowledge that we should have to know...Since, i gonna telling you about image analysis, you might ask me, what’s the difference between image analysis and image processing? Emmm.... how to explain...
ok, let add one more thing, which is image understanding, and see what [1] has been explaining as below;
* Image Processing : image in -> image out
* Image Analysis : image in -> measurements out
* Image Understanding : image in -> high-level description out
Could you understand what this guy trying to say?
Ok, macam nih, aku rasa, dalam computer vision ada 3 aspect yang perlu difahami oleh mereka yang ambik computer vision as they will be implementing those 3 things, which are, image processing, image analysis and image understanding. In general, those 3 things are playing with image as their input data but the output is different. Image processing takes an image as input but provide another image as the result. Example; take a colourful image (RGB), process it (say, threshold) and results are, it became a binary image (black for interested objects and white for background).
What about image analysis? Again, take an image as input data, process it (I think this usually involve maths formula such as Fourier Transform, Laplace Transform or etc), and the results are in numerical approach. I believe, the results are best performed in graph or table, well that way is easier to analyze, right?
And for the last part is image understanding. Remember, take an image as input data, and process it (usually identifies shape of the interest object in the image) and then recognize the shape and describe it. For example, the image shows a face of a person. Image understanding might describe where the location of the eyes, mouth, nose and etc of that person.
Ok, hubby aku nak ambik….hehehe…study kat rumah pulak…
And coretan seterusnya will be continue next week…
Ref :
[1] http://www.ph.tn.tudelft.nl/Courses/FIP/noframes/fip-.html
posted by Hidayah at 10/31/2004 01:48:00 AM
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