Biologi

Biologi adalah ilmu mengenai kehidupan. Istilah ini diambil dari bahasa Belanda "biologie", yang juga diturunkan dari gabungan kata bahasa Yunani, bios ("hidup") dan logos ("lambang", "ilmu"). Dahulu—sampai tahun 1970-an—digunakan istilah ilmu hayat (diambil dari bahasa Arab, artinya "ilmu kehidupan").

Obyek kajian biologi sangat luas dan mencakup semua makhluk hidup. Karenanya, dikenal berbagai cabang biologi yang mengkhususkan diri pada setiap kelompok organisme, seperti botani, zoologi, dan mikrobiologi.

Berbagai aspek kehidupan dikaji. Ciri-ciri fisik dipelajari dalam anatomi, sedang fungsinya dalam fisiologi; Perilaku dipelajari dalam etologi, baik pada masa sekarang dan masa lalu (dipelajari dalam biologi evolusioner dan paleobiologi); Bagaimana makhluk hidup tercipta dipelajari dalam evolusi; Interaksi antarsesama makhluk dan dengan alam sekitar mereka dipelajari dalam ekologi; Mekanisme pewarisan sifat—yang berguna dalam upaya menjaga kelangsungan hidup suatu jenis makhluk hidup—dipelajari dalam genetika.

Saat ini bahkan berkembang aspek biologi yang mengkaji kemungkinan berevolusinya makhluk hidup pada masa yang akan datang, juga kemungkinan adanya makhluk hidup di planet-planet selain bumi, yaitu astrobiologi. Sementara itu, perkembangan teknologi memungkinkan pengkajian pada tingkat molekul penyusun organisme melalui biologi molekular serta biokimia, yang banyak didukung oleh perkembangan teknik komputasi melalui bidang bioinformatika.

Content-based image retrieval

Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases.

"Content-based" means that the search will analyze the actual contents of the image. The term 'content' in this context might refer colors, shapes, textures, or any other information that can be derived from the image itself. Without the ability to examine image content, searches must rely on metadata such as captions or keywords, which may be laborious or expensive to produce.

HISTORY

The term CBIR seems to have originated in 1992, when it was used by T. Kato to describe experiments into automatic retrieval of images from a database, based on the colors and shapes present. Since then, the term has been used to describe the process of retrieving desired images from a large collection on the basis of syntactical image features. The techniques, tools and algorithms that are used originate from fields such as statistics, pattern recognition, signal processing, and computer vision.

TECHNICAL PROGRESS

There is growing interest in CBIR because of the limitations inherent in metadata-based systems, as well as the large range of possible uses for efficient image retrieval. Textual information about images can be easily searched using existing technology, but requires humans to personally describe every image in the database. This is impractical for very large databases, or for images that are generated automatically, e.g. from surveillance cameras . It is also possible to miss images that use different synonyms in their descriptions. Systems based on categorizing images in semantic classes like "cat" as a subclass of "animal" avoid this problem but still face the same scaling issues.Potential uses for CBIR include

• Art collections
• Photograph archives
• Retail catalogs
• Medical records

CONTENT COMPARISON TECHNIQUES

The sections below describe common methods for extracting content from images so that they can be easily compared. The methods outlined are not specific to any particular application domain.

COLOR

Examining images based on the colors they contain is one of the most widely used techniques because it does not depend on image size or orientation. Color searches will usually involve comparing color histograms, though this is not the only technique in practice.

TEXTURE

Texture measures look for visual patterns in images and how they are spatially defined. Textures are represented by texels which are then placed into a number of sets, depending on how many textures are detected in the image. These sets not only define the texture, but also where in the image the texture is located.

SHAPE

Shape does not refer to the shape of an image but to the shape of a particular region that is being sought out. Shapes will often be determined first applying segmentation or edge detection to an image. In some cases accurate shape detection will require human intervention because methods like segmentation are very difficult to completely automate

Sumber : www.wikipedia.org

Image retrieval using color and shape

Abstract

This paper deals with efficient retrieval of images from large databases based on the color and shape content in images. With the increasing popularity of the use of large-volume image databases in various applications, it becomes imperative to build an automatic and efficient retrieval system to browse through the entire database. Techniques using textual attributes for annotations are limited in their applications. Our approach relies on image features that exploit visual cues such as color and shape. Unlike previous approaches which concentrate on extracting a single concise feature, our technique combines features that represent both the color and shape in images. Experimental results on a database of 400 trademark images show that an integrated color- and shape-based feature representation results in 99% of the images being retrieved within the top two positions. Additional results demonstrate that a combination of clustering and a branch and bound-based matching scheme aids in improving the speed of the retrievals.

sumber : http://www.sciencedirect.com/

Hiding in plain sight

The little-known technique of steganography provides a stealthy way to conceal data in other text.

By Kevin D. Weeks

As I recall, it was my grandmother who first introduced my sister and me to using lemon juice as invisible ink. You might remember the technique from your childhood: You dip a paper matchstick in lemon juice and write with it. You can't see anything until you hold your writing paper over a candle, which magically turns the lemon juice brown, revealing the hidden writing. We had great fun with it until our mother caught us playing with matches, candles, and paper. So much for my first foray into steganography.

At the time, though, I didn't know I was engaged in steganography -- from the Greek, meaning "covered writing." In fact, I didn't know hiding messages had a name at all until I ran across an article by Richard Stallman that mentioned steganography. I'm not used to encountering unfamiliar terms, so I looked it up. Never ask a word lover to do research on the Web. Finding a new word means research will stop until the word's meaning is tracked down.

Hiding in plain view

Digital steganography is based on the fact that artifacts like bitmaps and audio files contain redundant information. That's why lossy compression techniques such as JPEG and MP3 work. Such techniques eliminate part of the redundancy, allowing the image or wave file to be compressed. The idea behind steganography is that instead of eliminating the redundant information, you replace it with other data.

For example, suppose the first eight bytes of an image were:

10001001 11101001 11101001 10011011

10011011 10001001 00011111 00011101

A simple steganographic program could hide the letter S (01010011) by changing the least significant bit in each of the first eight bytes to reflect the binary letter. The result:

10001000 11101001 11101000 10011011

10011010 10001000 00011111 00011101

The graphic above demonstrates that when this technique is properly applied, its effects on the resulting image are almost impossible to detect. You could receive a message I'd embedded in a graphic, but no one else could make out more than an image.

Cryptic complement

Steganography isn't meant to replace cryptography, but to complement it; its purpose is to avoid raising suspicions. Returning to my invisible ink example, suppose I was having an affair with my maid (let's name her Angelique). I want to tell Angelique how beautiful she is, but don't want my wife to find out. I could write Angelique a love letter using invisible ink. Switching to visible ink, I could then write another note (perhaps asking her to pick up my laundry) over the secret message. Should my wife find it, she would see only a banal exchange about housekeeping matters. Angelique, expecting more, would hold my note over a candle to expose the hidden message.

If I were concerned that my wife might already be suspicious, I would take further security steps, such as using a less easily-discovered ink. Like a suspicious wife looking for secret messages, analysis techniques can penetrate a simple bit-swapping scheme. A plain text message such as the one earlier described has detectable patterns.

I used a freeware tool named S-Tools to hide this article in the second bitmap. (You can find a number of steganographic programs, including S-Tools, at www.blackhat.org/stego.htm.) By default, S-Tools first compresses the data you want to hide. Compression does little on its own to further hide the data -- it simply makes it easier to store larger documents. However, S-Tools then encrypts the data using a pass phrase that you stipulate.

Now detecting the hidden message is like looking for a needle in a haystack. A sufficiently sophisticated analysis might still detect the concealed text, though, so some steganographic tools go a step further. Such tools can analyze multiple files, looking for the one that will change the least when a given message is hidden in it. Think of it as hiding a needle in a gray haystack. Even if the message were found, it would still have to be decrypted.

More sophisticated steganographic techniques exist and are used in a number of commercial tools. Some of these tools rely on JPEG or MP3 -- lossy compression algorithms -- to make the hiding technique even more effective.

For more information on steganography, check out Steganography Info and Archive and a white paper titled Steganography by Neil F. Johnson. There's a commercial product named the Steganos II Security Suite that will encrypt and hide data on your computer. If you're interested in source code for steganography programs, contact Andy Brown, the author of S-Tools, and he'll sell you the source for his tool. Or you can download a Java program including source from Romana Machado, a most unusual software engineer.

sumber : http://dn.codegear.com