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Structure your queries to make sure that MySQL will be able to use an index. Avoid wrapping functions around indexed columns, as in the following poor SQL query, which filters order from the last seven days: SELECT * FROM customer_orders WHERE TO_DAYS(order_created) TO_DAYS(NOW()) <= 7; Instead, rework the query to isolate the indexed column on the left side of the equation, as follows: SELECT * FROM customer_orders WHERE order_created >= DATE_SUB(NOW(), INTERVAL 7 DAY); In the latter code, the function on the right of the equation is reduced by the optimizer to a constant value and compared, using the index on order_created, to that constant value. The same applies for wildcard searches. If you use a LIKE expression, an index cannot be used if you begin the comparison value with a wildcard. The following SQL will never use an index, even if one exists on the email_address column: SELECT * FROM customers WHERE email_address LIKE '%aol.com'; If you absolutely need to perform queries like this, consider creating an additional column containing the reverse of the e-mail address and index that column. Then the code could be changed to use a wildcard suffix, which can be used by an index, like so: SELECT * FROM customers WHERE email_address_reversed LIKE CONCAT(REVERSE('aol.com'), '%');

Image processing is a complicated art whose success greatly depends on the design of the imaging task. In this case, processing is simplified by positioning the camera just a few inches from the user s wrist and only having to identify rectangular blobs of simple colors. One complication is the background: the user s hand, arm, shirt, and head (as shown in Figure 10-3). For example, in early tests a red blob kept being detected even when the wrist strap s yellow band was right in front of the camera. This was triggered by the user s red shirt, which occupied a comparatively large part of the image. Another problem is the lighting environment. Overhead lights can cause leeching out of color, caused by excessive reflection. This makes it more difficult to find the color bands. Different webcams generate slightly different images. For instance, the camera attached to my second test machine produces a slightly greener image. This makes green a bad choice for a band color, since so much of the background has a similar hue.

This is quite a lot of effort for a single simple page and clarifies why a single code base for both Silverlight environments is not practical. After completing these steps, your project should compile without errors, though it still shows nothing when run because we just get to see the empty frame. To actually display MainPage, we simply need to tell the frame to navigate there. Modify the HostPage class constructor to contain the code shown in Listing 16 12. Listing 16 12. Instructing the Frame to navigate to MainPage public HostPage() { InitializeComponent(); // Navigate to MainPage hostFrame.Navigate(new Uri("/MainPage.xaml", UriKind.Relative)); } Now when you run the application, the browser window appears and displays the contents of MainPage. These are the basic steps that need to be performed to transfer your pages across to Silverlight from the phone. Once you have followed these steps, the majority of the XAML layout and the code behind the page should work with little or no modification (unless you are calling in to any Windows Phone 7 libraries, in which case they will need to be redesigned or refactored).

Summary

Most image processing applications support a configuration/testing stage so the hardware and software parameters can be tweaked; I employ a similar strategy here. In the next section, I describe the FindBands application, which analyzes webcam images without affecting a Java 3D scene. FindBands acts as a test rig for the image processing classes utilized in this chapter s main example, BandObjView3D. BandObjView3D converts the wrist strap data into navigational commands for exploring a 3D scene, and is described in the Arm Navigation section later in this chapter.