I'm not sure I can find your quote, but I can mention a few books of the past 30 years that leaned at least somewhat toward the practical advice rather than toward the more purely theoretical/mathematical/snooty. (One of the more "theoretical" textbooks I've read simply regurgitated pages of math from an earlier textbook, complete with the exact same glaring typo.)
Digital Picture Processing by Rosenfeld and Kak is a classic. My editions of Volume 1 and Volume 2 have a copyright of 1982. Volume 1 covers more of the fundamentals of the mathematics & image formation, and Volume 2 digs into practicalities of segmentation, matching, etc.
Computer Vision by Ballard and Brown, also from 1982, is even today a useful reference for those who have to make a vision system work. This book is a bit friendlier in terms of presenting real images and also color plates. There are pseudocode algorithms and several useful formula (e.g. RGB to HSI color space). They make a number of useful practical points about the application of algorithms, and they might have written something similar to the quote you mention.
Applying Machine Vision by Nello Zuech was published in 1988. My later edition is named Understanding and Applying Machine Vision. Unlike the other books I mention, Zuech's book is more of a practical guide for engineers who have to specify, install, maintain, and possibly modify vision systems. The list price for Zuech's book is $200 on Amazon, but if you do a search you may find other sources. He has so many checklists, decision matrices, etc., that the book is great as a general reference. That book or something else Zuech wrote could have been your source.
Digital Image Processing by Gonzalez and Woods (1st edition 1992) is a commonly used textbook, and it's reasonably chatty in tone, although there's not much (that I remember) about system integration or lighting. Also check out their website http://www.imageprocessingplace.com/.
Machine Vision: Theory, Algorithms, Practicalities by E.R. Davies (1st edition 1990, 3rd edition, 2006) is one of the better textbooks examining the real work required to solve an application. The algorithms as a rule are the simpler ones, but Davies digs in and examines not only where an algorithm might be applied, but the practical results of doing so. That said, it's probably too recent to be your source.
Of all those, Zuech's book is most oriented to the practical assessment of a complete system. Even if he's not your source, it's good to have a copy of his work.