FINAL DESIGN STATEMENT DESIGN STATEMENT The intent of this Project is to explore the illusion of depth in images. More specifically, our project will focus on how depth changes as sizes and color combinations change. Depth is a very important concept in image design, and variations on elements of an image can affect the depth perceived by the viewer. We suppose that contrasting colors may bring figures to the front or send them to the background of the image, while monochromatic design can flatten the image removing the illusion of depth. Colors with contrasting values can heighten positive space, increasing the depth in the image. Solid objects in positive space tend to “stand out,” or provide dimension, due to resembling real life objects. When solid objects are colored in a contrasting hue to the positive space, the affect is well defined. We will use shapes of circle, polygon and pentagram. Outlined figures, transparent figures, combined with negative space do not provide a sense of depth, and blend in with the background unless drawn in a contrasting, dynamic color. Depth can also be emphasized through the contrasting shapes and sizes of image elements. Smaller image elements generate more depth, and create a unique, mysterious image. Polygons have “fatter,” fuller bodies that resemble circles, while polygrams are star-like and leave space between the blades. We also investigate how that variation effects depth, along with a variety of side numbers, in order to make the polygons rounder and the polygrams sharper, and study the depth in those images. Originally, we meant to fill the entire body of a pentagram, but we chose to fill in the blades. This further explores our concept of diversity. Hexagrams and octagrams are completely filled in. The texture of our images is plain and uniform. The colors vary in order to check the differences in perceived depth and emphasis. We explore the following color combinations: monochromatic, complementary, contrasting and analogous. Another variation considered is the proportion of the positive space to the negative space. Our picture plane is the canvas that we draw on, and the positive shape is the middle shape, and negative space/shape is a rectangle with the same size as canvas and filled with designated color. We also use lines to enclose a shape. The shape is especially emphasized, since it’s placed in the center of the picture. TECHNIQUE STATEMENT We made use of GIMP tools to operate on the shape, numeric operation to pair up the combination and scale images, and the technique of list to select colors.​ The first algorithmic technique we used is vectors, which help us track the points a turtle has passed through, and use them to select and fill the shape. Our code begins with two vectors. The first vector contains all of the corners or points, of a given shape. This vector assures that the background is colored. The second vector contains the corner that is recorded. Our code includes a procedure that takes two parameters, an image and a number. The procedure binds values to a range of variables. The variables are determined by the number taken as input, and for each input it takes its remainder with a different prime number, so that the combination is unique each time. The procedure also binds two lists of colors which are used in our selection of colors for the shape and background. The procedure then fills the background of the image with a color taken from the list of background colors. Which colors are chosen from the list depend on the number inputted, and the variable that was assigned a value for color. The brush (foreground color) is set to a color picked from a different list for foreground colors and then continues to check whether that variable is equal to 0. If it is 0, it selects an ellipse centered in the center of the image, with diameters equal to a half of the image height and width, respectively. It then fills the ellipse with the foreground color. If it is 1, it uses a turtle procedure that creates a turtle that repeats the steps of going forward and turning a number of degrees, so that it draws a polygram with a number of sides that is equal to 5, 6 or 8. This number of sides is determined from a variable that was bound in the beginning. The number of sides is calculated by using a series of numeric procedures that successfully turns 0 to 5, 1 to 6 and 2 to 8. If the shape variable is 2, then the procedure follows a similar path, calling a procedure that uses different numbers for turning the turtle, so that the final shape is a polygon instead of a polygram. It uses the same technique of converting 0-1-2 to 5-6-8 for the number of sides. If the shape variable is 3, then the procedure creates a set of points by using a turtle to follow the shape of a polygon, according to the image’s height, width, and the number of sides, that represent the points where the corners of the polygon are. If the shape variable is 4 then the procedure creates a set of points by drawing a polygram and recording the points at which the turtle stops, according to the image’s height, width, and the number of sides, that represent the points where the corners of a polygram or star are. The polygram is then filled using GIMP tools. If it is a hexagram or octagram, then it is filled completely. If it is a pentagram, then the blades, rather than the core, are filled. Depending on the aspect ratio of the image, the produced shape might not scale appropriately. This is because the procedure is coded to work with 1:1 aspect ratio. Ratios lesser than that might work, but not actually scale. This is because we use turtles, which are very hard to be used for scaled drawings. Ellipses scale appropriately to every aspect ratio, because they are independent of turtles. Algorithmic techniques used: Gimp tools to draw and color on images, vectors to count and record points, conditionals to determine which type of shape will be drawn, numeric operations to decide and cycle through combinations, or transform numbers. This procedure produces a wide variety of completely unique images. By using conditional clauses and varying many different things each time that the procedure is run with a different number, we can ensure that the range of 0-999 of inputs produces 1000 unique images. This is ensured by the fact that we include 3 variations in side number, 5 variations in shape type, 7 variations in background color and 11 variations in foreground color. By using simple combinatorics, and ensuring that all those variations are independent by the use of prime numbers and correctly organized conditionals, we can show that the procedure produces 3*5*7*11 unique combinations, which results in 1155 distinct images, above the 1000 requisite.