Advantages and Disadvantages of Graphinder

Having analyzed the different internal aspects of the project, we will comment on the capacities and limitations of its operation. These are the advantages and disadvantages of a pilot experience in the use and systematics of the Internet, a field yet to be fully discovered. The initial purpose is creating a beta version that, in the neat future, could become a tool for a wide group of people, to be used at work or during their spare time.

Firstly, we will mention the EFFICIENT QUALITIES that we - hypothetically - find in graphinder. The different aspects related to the methodology of the image, to its construction, will be considered at all times. Thus, this methodology becomes the mediator of exclusive procedures based on a wide set of areas.

ADVANTAGES

General Level:
Selective search of information based on graphic data

On several occasions, when working with iconographic documents, we do not have data on the manipulated images. Therefore, we need one or more reliable references to provide us of a starting point from which to access all the data available in the Internet on the field of the illustration, drawing or photograph. This is the original, main and virtually sole purpose of inventing graphinder. To this essential and strictly informative function created to aid the cyberspace community involved in certain professional activities, we add a second one. This second function could be described from a more technical point of view, as the necessity of including new archetypes of the visual alphabet in the data processing that occurs inside the channels in charge of regulating the information that gets to our terminals.

graphinder completes and refines the systematics of the search

graphinder would provide a tool that covers most of the data searching spectrum of the world wide web, at least until the invention of a search engine that recognizes sound entries following the philosophy described in this paper. Chains of characters and images or, in other words, typographical expressions and iconographic representations, will fulfill all their needs of information trasmission from the internal channels of the Internet, where they live.

Technical Level:
Verification of images already included in the net (STABLE images)
for their comparison with the new ones (INPUT images)

It is not necessary to verify each one of the images in the Internet -which would be nearly impossible- because their original or new digital structure bears their genetic ID in numeric values. These values refer to the color attributes that characterize each one of the pixels that make up its appearance.

... and, in ascending order according to the ranking that classifies the obstacles encountered, these are the DISADVANTAGES.

DISADVANTAGES

General / Technical Level:
Less spontaneous introduction of data in the initial phase.
Availability of essential devices

The idea of substituting the elemental – or spontaneous - action of introducing a certain quantity of text related to an inquiry in the search engine or browser, with the action suggested for this new system, in which the data come from graphic formats (bitmaps), reveals a first significant load or hindrance that we must overcome to achieve our goals.

On the other hand, acquiring the said graphinder interface is not enough. We must also have access to a series of hardware devices (digital camera or scanner) and image processing programs, which will permit the manipulation of the document to best adapt it to the search method. Nevertheless, we assume that the graphinder user has an unquestionable practice in operating with this type of visual entities, and owns the abovementioned physical tools as part of his/her work equipment. In any case, it should be mentioned that the initial course of this search engine follows the same steps as other experimentations, such as Internet 2, created in and for the academic research bodies. This circumstance reduces the original number of people interested in the engine and increases its capacity for this kind of applications.

Technical Level:
Physical difficulties in the recognition of the data to be verified

The main obstacle for matching the models is that, in 99% of the cases, the graphic information we have will be physically distorted or imbalanced when compared with the image that is uploaded in the Internet. An example that corroborates this fact is explained below (see illustration 8 for more information):

We receive a printed photograph with a fragment of a painting by Eduardo Paolozzi called Bash. Although I am giving the name of the author and the work, we do not know these data upon receiving the photograph and, eager for obtaining information about this image we find so attractive, we begin our research based on what we have, a small color piece probably torn from an art handbook. Following the steps described above, we scan the image using a 1:1 scale to transform it into a digital document. After repeating several digitalization operations on the same piece, we obtain the same number of graphic files. These, when compared among them, show slight alterations of color (see the numeric equivalences in illustration 8, detail “A” and “B”).

We could perform an infinite number of verifications on this argument, and the above fact would still be the same: two digital documents that refer to the same iconographic representation do not have to show the same chromatic values, as the level of manipulation they suffered when converted to the binary format could be - and most probably was - different in each case. Therefore, it is necessary to solve the problem of identifying both images as the same document (input image = stable image), overcoming the numeric eventualities or mismatches that affect each image.

The solution is creating a method of graphic recognition based on the numerical comparison of the pixel values. This application must establish a general average of the values for all the pixels that correspond to both images (input and stable), and then generate a table of figures which will be proportional to the set of points that shape both matrixes (algorithm for the interpolation of pixels).

After our investigation, whose introduction was the appearance of that small piece of paper, we obtain a valuable list of references about the author of the previously unknown work. The artist has Italian name and ancestors, but is of Scottish nationality; he was one of the first Pop Art painters in the 50s. This information has been extracted from the web after processing a tiny graphic excerpt.

Illustration 9
Comparison of pixeled areas from two reproductions of the same image. Manuel Viñas Limonchi

Up to this point, we have analyzed the difficulties that could arise due to a possible difference in the color attributes of two equal graphic documents. However, as a rule, the various copies of the same image that we can find in books, newspapers, CD-ROMs, ... appear in different levels of graphic resolution or size. This indicates that the resolution of the fragment or image introduced will probably be different from the resolution of the web images. In other words,

INPUT IMAGE Size STABLE IMAGE Size

This is the case with images such as drawings or pictorial representations made using traditional instruments and then digitalized by means of the known devices. These are not usually “uploaded” to the Internet servers with their actual size, as they would take too much space and therefore give problems for storage and user’s manipulation (slow screen display and downloading). These inconveniences are magnified in countries such as Spain where, due to technical problems, the transmission of data through the network protocols does not reach the speed we would all like.

On the other hand, it is more usual - although we cannot generalize - to find originally digital works (synthetic images) in the web with their actual sizes. This circumstance would make our search process much easier.

After all these incidents, the same image, processed and then examined using different media, acquires different graphic imprints from the personal marks added by each digital mechanism. Thus, the quantity of dots per inch (dpi) of its total area and its chromatic values - as mentioned above - vary. This is the main dilemma that will hinder the ideal projection of graphinder. A possible solution could be developing a relational algorithm that compares -interpolating color pixels- this discrepancy on the quantity and quality (attributes) of the pixels that shape both copies (illustration 9).

... in short

We are talking about a new intelligent agent, graphinder, inserted in the methodological stage that regulates the information search systematic in the vast cosmos of the Internet. An innovative network knowledge management system, whose last purpose is offering services for transmitting communication habits to any “cyber-consumer”, using the semantic faculties of the graphic element.

Fortunately, the digital technology allows us to appear in the Internet with first and last names, photos, videos, electronic identities before and after the @, etc. But, above all, we are just numbers. This is the most outstanding characteristic of an electronic environment as peculiar as the Internet and, oddly enough, one of the less considered, even though it has a devastating impact on all its users.
(Luis A. Fernández Hermana)